Package 'poliscidata'

Title:	Datasets and Functions Featured in Pollock and Edwards, an R Companion to Essentials of Political Analysis, Second Edition
Description:	Bundles the datasets and functions used in the textbook by Philip Pollock and Barry Edwards, an R Companion to Essentials of Political Analysis, Second Edition.
Authors:	Barry Edwards and Philip Pollock
Maintainer:	Barry Edwards <[email protected]>
License:	CC0
Version:	2.3.0
Built:	2024-11-27 06:54:04 UTC
Source:	CRAN

Help Index

Calculates adjusted R-Squared statistic
Imported Functions Made Available to Users
Calculates a 95 Percent Confidence Interval
Calculates a 99 Percent Confidence Interval
Displays R Colors
Column Percentages
Calculates a statistic for measure of association in cross-tabulation
Calculates Cramer's V
Calculates model fit statistics for a svyglm weighted regression model
Generates table and figure describing distribution of variable values.
GSS dataset for R Companion to Essentials of Political Analysis, Second Edition
GSS design dataset for R Companion to Essentials of Political Analysis, Second Edition
Controlled Mean Comparison Table
Calculates predicted probability for a given logged odds value
Interaction plot
Displays line types for R plots
Logistic regression model statistics
NES dataset for R Companion to Essentials of Political Analysis, Second Edition
NES design dataset for R Companion to Essentials of Political Analysis, Second Edition
Translate logistic regression coefficients into odds ratios
Comparing Logistic Regression Models with Chi-Squared Test
Displays plotting characters available in R
Plots mean comparison
Prints html-ready table to local working directory
Difference of Proportions Test
Prints string to console quickly
Sets contrasting color for text
Prints string to console slowly
Calculates Somer's D
Returns case-level information in order
States dataset for R Companion to Essentials of Political Analysis, Second Edition
States design dataset for R Companion to Essentials of Political Analysis, Second Edition
Computes summary statistics
Chi-Squared Statistic for Relationship Between Categorical Variables using Weighted Dataset
Produces summary statistics
Function to Introduce Users to R Companion Environment
World dataset for R Companion to Essentials of Political Analysis, Second Edition
World design dataset for R Companion to Essentials of Political Analysis, Second Edition
Weighted Box Plot
Find Median of Variable
Find Mode of Variable
Find Standard Deviation of Variable
Weighted T-Test
Controlled cross tabulation analysis with optional weights
Cross tabulation Analysis
Cross tabulation Analysis with Chi-Squared Statistic

Calculates adjusted R-Squared statistic

Description

Calculates adjusted R-Squared statistic based on user-defined inputs. This function can be used after estimating a model that does not report adjusted R-Squared statistic. For svyglm model fit statistics, see fit.svyglm function documentation.

Usage

AdjR2(tdf, null.dev, resid.dev, k)
AdjR2(tdf, null.dev, resid.dev, k)

Arguments

`tdf`	The total degrees of freedom
`null.dev`	The null deviance or total sum of squares
`resid.dev`	The residual deviance or error sum of squares
`k`	The number of parameters used (to reduce deviance)

Value

Returns an adjusted R-Squared statistic, a numeric value between 0 and 1

Examples

   AdjR2(200, 1500, 1100, 5)
   
   AdjR2(tdf=200, null.dev=1500, resid.dev=1100, k=5)
AdjR2(200, 1500, 1100, 5)
   
   AdjR2(tdf=200, null.dev=1500, resid.dev=1100, k=5)

Imported Functions Made Available to Users

Description

The compmeans function is imported from descr package. See compmeans documentation for details.

The crosstab function is imported from the descr package. See crosstab documentation for details.

The csv.get function is imported from the Hmisc package. See csv.get documentation for details.

The cut2 function is imported from the Hmisc package. See cut2 documentation for details.

The ddply function is imported from the plyr package. See ddply documentation for details.

The describe function is imported from the Hmisc package. See describe documentation for details.

The freq function is imported from the descr package. See freq documentation for details.

The plotmeans function is imported from the gplots package. See plotmeans documentation for details.

The scatterplot function is imported from the car package. See scatterplot documentation for details.

The spss.get function is imported from the Hmisc package. See spss.get documentation for details.

The stata.get function is imported from the Hmisc package. See stata.get documentation for details.

The svyboxplot function is imported from the survey package. See svyhist documentation for details.

The svyby function is imported from the survey package. See svyby documentation for details.

The svychisq function is imported from the survey package. See svychisq documentation for details.

The svydesign function is imported from the survey package. See svydesign documentation for details.

The svyglm function is imported from the survey package. See svyglm documentation for details.

The svymean function is imported from the survey package. See surveysummary documentation for details.

The svyplot function is imported from the survey package. See svyplot documentation for details.

The svytable function is imported from the survey package. See svychisq documentation for details.

The wtd.chi.sq function is imported from the weights package. See wtd.chi.sq documentation for details.

The wtd.cor function is imported from the weights package. See wtd.cor documentation for details.

The wtd.hist function is imported from the weights package. See wtd.hist documentation for details.

The wtd.mean function is imported from the Hmisc package. See wtd.stats documentation for details.

The wtd.quantile function is imported from the Hmisc package. See wtd.stats documentation for details.

The wtd.t.test function is imported from the weights package. See wtd.t.test documentation for details.

The wtd.var function is imported from the Hmisc package. See wtd.stats documentation for details.

Usage

compmeans(...)

crosstab(...)

csv.get(...)

cut2(...)

ddply(...)

describe(...)

freq(...)

plotmeans(...)

scatterplot(...)

spss.get(...)

stata.get(...)

svyboxplot(...)

svyby(...)

svychisq(...)

svydesign(...)

svyglm(...)

svymean(...)

svyplot(...)

svytable(...)

wtd.chi.sq(...)

wtd.cor(...)

wtd.hist(...)

wtd.mean(...)

wtd.quantile(...)

wtd.t.test(...)

wtd.var(...)
compmeans(...)

crosstab(...)

csv.get(...)

cut2(...)

ddply(...)

describe(...)

freq(...)

plotmeans(...)

scatterplot(...)

spss.get(...)

stata.get(...)

svyboxplot(...)

svyby(...)

svychisq(...)

svydesign(...)

svyglm(...)

svymean(...)

svyplot(...)

svytable(...)

wtd.chi.sq(...)

wtd.cor(...)

wtd.hist(...)

wtd.mean(...)

wtd.quantile(...)

wtd.t.test(...)

wtd.var(...)

Arguments

...

See source package help file for details on function usage.

Calculates a 95 Percent Confidence Interval

Description

Prints the lower and upper boundaries of a 95 Percent confidence interval. Also see the CI95 function.

Usage

CI95(m, se)
CI95(m, se)

Arguments

`m`	A single number equal to the mean value of a statistic.
`se`	single number equal to the standard error of the statistic.

Value

Returns the 95

Examples

 
  CI95(10, 1)
  
  CI95(m=8, se=2)
CI95(10, 1)
  
  CI95(m=8, se=2)

Calculates a 99 Percent Confidence Interval

Description

Prints the lower and upper boundaries of a 99 Percent confidence interval. Also see the CI95 function.

Usage

CI99(m, se)
CI99(m, se)

Arguments

`m`	A single number equal to the mean value of a statistic.
`se`	single number equal to the standard error of the statistic.

Value

Returns the 99

Examples

 
  CI99(10, 1)
  
  CI99(m=8, se=2)
CI99(10, 1)
  
  CI99(m=8, se=2)

Displays R Colors

Description

Produces plot of colors available in R. Colored cells labels with numeric value that corresponds to that color. No values supplied to function.

Usage

Colors()
Colors()

Value

No value returned

Examples

  Colors()
Colors()

Column Percentages

Description

Generates column percentaged tables for multi-dimensional controlled cross-tabulations, based on function by John Fox. Used by xtabC function.

Usage

colPercents(tab, digits = 2)
colPercents(tab, digits = 2)

Arguments

`tab`	A table of values
`digits`	Number of decimal places to display, default is 2.

Value

Table of column-percentaged values

Calculates a statistic for measure of association in cross-tabulation

Description

This function is called by tablesomersDC function.

Usage

compADPQ(x)
compADPQ(x)

Arguments

`x`	A matrix or data frame

Value

Returns a list of statistics

Calculates Cramer's V

Description

Calculates Cramer's V, a measure of association to gauge the strength of the relationship between two nominal-level variables. A score of 0 indicates no relationship; a score of 1 indicates a perfect relationship.

Usage

CramersV(chi, r, c, n)
CramersV(chi, r, c, n)

Arguments

`chi`	A number equal to the Chi-Squared statistic
`r`	A number equal to the number of rows
`c`	A number equal to the number of columns
`n`	A number equal to the sample size

Value

The Cramer's V statistic, a number between 0 and 1.

Examples

  CramersV(84.18, 2, 2, 1315)
  
  CramersV(chi=84.18, r=2, c=2, n=1315)
CramersV(84.18, 2, 2, 1315)
  
  CramersV(chi=84.18, r=2, c=2, n=1315)

Calculates model fit statistics for a svyglm weighted regression model

Description

Model fit statistics for a svyglm weighted regression model

Usage

fit.svyglm(svyglm, digits = 3)
fit.svyglm(svyglm, digits = 3)

Arguments

`svyglm`	An object of type svyglm. This object is the output of the svyglm functon.
`digits`	Number of digits to report after decimal place, optional (default = 3).

Value

Returns a numeric vector of R-Squared and Adjusted R-sSquared statistics.

Examples

   library(poliscidata)
   
   obamaThermModel <- svyglm(obama_therm ~ gender, design=nesD, na.action="na.omit")
   summary(obamaThermModel)
   fit.svyglm(obamaThermModel)
library(poliscidata)
   
   obamaThermModel <- svyglm(obama_therm ~ gender, design=nesD, na.action="na.omit")
   summary(obamaThermModel)
   fit.svyglm(obamaThermModel)

Generates table and figure describing distribution of variable values.

Description

Generates frequency distribution table and bar chart to describe distribution of variable values. Based on freq function in descr package.

Usage

freqC(x, w, plot = TRUE)
freqC(x, w, plot = TRUE)

Arguments

`x`	A vector of variable values, should be in form dataset$var
`w`	Sample weights (optional), should be in form dataset$weighvar
`plot`	Do you want a bar chart? (default set to TRUE)

Value

A frequency distribution table (a "freqtable" and "matrix" class object)

Examples

   library(poliscidata)
   
   freqC(gss$zodiac, gss$wtss)
   
   freqC(x=gss$zodiac, w=gss$wtss)
library(poliscidata)
   
   freqC(gss$zodiac, gss$wtss)
   
   freqC(x=gss$zodiac, w=gss$wtss)

GSS dataset for R Companion to Essentials of Political Analysis, Second Edition

Description

The General Social Survey polls individuals about their attitudes and beliefs. This dataset is used to demonstrate application of R to political analysis. See book Appendix for variable names and descriptions.

Usage

gss
gss

Format

A data frame with 1974 rows and 221 variables.

abany: Abortion Permissible: Woman Wants For Any Reason
abdefect: Abortion Permissible: Strong Chance of Serious Defect
abhlth: Abortion Permissible: Woman's Health Seriously Endangered
abnomore: Abortion Permissible: Woman Married–Wants No More Children
abortion: Under How Many Conditions Abortion Permissible?
abortion_3: Under How Many Conditions Abortion Permissible? 3 Categories
abpoor: Abortion Permissible: Low Income–Can't Afford More Children
abrape: Abortion Permissible: Pregnant As Result of Rape
absingle: Abortion Permissible: Not Married
affrmact: Favor Preference in Hiring Blacks
affrmact2: Support Affirmative Action?
age: Respondent's Age
age.f: Respondent's Age (as ordered factor)
age2: Respondent's Age: 2 Categories
age_3: Age Group: 3 Categories
age_5: Age Group: 5 Categories
attend: How Often Respondent Attends Religious Services
attend2: Attendance at Religious Services: Low or High
attend3: Attendance at Religious Services: 3 Categories
attend7: Attendance at Religious Services: 7 Categories
authoritarianism: Authoritarianism Scale
bible: Feelings About the Bible
black: Is Respondent African American?
black_traits: Black Stereotypes
born: Was Respondent Born in This Country
cappun: Favor or Oppose Death Penalty For Murder
childs: Number of Children
closeblk: How Close Do You Feel to Blacks?
closeblk2: How Close to Blacks? 2 Categories
closewht: How Close Feel to Whites
closewht2: How Close Do You Feel to Whites? 2 Categories
cohort: Year of Birth
colath: College Teaching: Allow Anti-Religionist to Teach
colcom: College Teaching: Should Communist Teacher Be Fired
colhomo: College Teaching: Allow Homosexual to Teach
colmil: College Teaching: Allow Militarist to Teach
colmslm: College Teaching: Allow Anti-American Muslim Clergymen to Teach
colrac: College Teaching: Allow Racist to Teach
con_govt: Confidence in Government Institutions
conarmy: Confidence in Military
conbus: Confidence in Major Companies
conclerg: Confidence in Organized Religion
coneduc: Confidence in Education
confed: Confidence in Exec Branch of Fed Government
confinan: Confidence in Banks & Financial Institutions
conjudge: Confidence in United States Supreme Court
conlabor: Confidence in Organized Labor
conlegis: Confidence in Congress
conmedic: Confidence in Medicine
conpress: Confidence in Press
consci: Confidence in Scientific Community
contv: Confidence in Television
courts: Courts Dealing With Criminals
dateintv: Date of Interview
degree: Respondent's Highest Degree
dem: Is Respondent a Democrat?
divlaw: Divorce Laws
divlaw2: Should divorce laws make it more difficult?
educ: Highest Year of School
educ_2: Education: 2 Categories
educ_4: Education: 4 Categories
egalit_scale: Egalitarianism Scale
egalit_scale3: Egalitarianism: 3 Categories
egalit_scale4: Egalitarianism: 4 Categories
eqwlth: Should Government Reduce Income Differences?
ethnic: Country of Family Origin
evangelical: Evangelical Scale
fechld: Female Roles: Mother Working Doesn't Hurt Children
feelevel: Amount of Fees Paid (to Respondent for Interview)
feeused: Fee Given to Get Case (for the Interview)
fefam: Female Roles: Better For Man to Work, Woman Tend Home
femrole: Female Role (Scale of Values)
femrole2: Female Role: 2 Categories
fepresch: Female Roles: Preschool Kids Suffer If Mother Works
fucitzn: Is Respondent Planning/Applying For US Citizenship?
fund: How Fundamentalist Is Respondent Currently?
fund2: Is Respondent Fundamentalist?
getahead: Opinion of How People Get Ahead
god_r: Know God Exists?
grass: Should Marijuana Be Made Legal?
grass.legal: Should Marijuana Be Made Legal? (numeric)
gunlaw: Favor or Oppose Gun Permits?
happy: General Happiness
helpblk: Should Government Aid Blacks?
helpnot: Should Government Do More or Less?
helpoth: To Help Others
helppoor: Should Government Improve Standard of Living?
helpsick: Should Government Help Pay For Medical Care?
hhtype1: Household Type (Condensed)
hispanic: Hispanic Specified
hispanic_2: Is Respondent Hispanic?
homosex: Homosexual Sex Relations
homosex2: Homosexuality Always Wrong?
id: Respondent Id Number
income06: Total Family Income
int_info_scale: Interest in Current Issues? (Additive index)
intage: Interviewer: Age of Interviewer
intecon: Interested in Economic Issues?
inteduc: Interested in Local School Issues?
intenvir: Interested in Environmental Issues?
intethn: Interviewer: Race of Interviewer
intethn_2: Interviewer: Interviewer's Race
intfarm: Interested in Farm Issues?
inthisp: Interviewer: Is Interviewer Spanish, Hispanic or Latino
intintl: Interested in International Issues?
intmed: Interested in Medical Discoveries?
intmil: Interested in Military Policy?
intrace1: Interviewer: Interviewer's Race1
intrace2: Interviewer: Interviewer's Race2
intrace3: Interviewer: Interviewer's Race3
intsci: Interested in New Scientific Discoveries?
intsex: Interviewer: Sex of Interviewer
intspace: Interested in Space Exploration?
inttech: Interested in Technologies?
intyrs: Interviewer: Years of Service as an Interviewer at NORC
kids: Does Respondent Have Kids?
libath: Allow Anti-Religious Book in Library?
libcom: Allow Communists Book in Library?
libhomo: Allow Homosexuals Book in Library?
libmil: Allow Militarists Book in Library?
libmslm: Allow Anti-American Muslim Clergymen's Books in Library?
librac: Allow Racists Book in Library?
lngthinv: How Long Was Interview
marital: Marital Status
militarist_tol: Tolerance Toward Militarists
mobile16: Geographic Mobility Since Age 16
mode: Interview Done In-Person or Over the Phone
mslm_col: Muslims: Teach in College?
mslm_lib: Muslims: Book in Library?
mslm_spk: Muslims: Preach?
mslm_spk.yes: Muslims: Preach? (as numeric)
mslm_spk.high: Muslims: Preach? (as numeric)
nataid: Federal spending: Foreign Aid
natarms: Federal spending: Military, Armaments, and Defense
natchld: Federal spending: Assistance for Childcare
natcity: Federal spending: Solving Problems of Big Cities
natcrime: Federal spending: Halting Rising Crime Rate
natdrug: Federal spending: Dealing with Drug Addiction
nateduc: Federal spending: Improving Nations Education System
natenrgy: Federal spending: Developing Alternative Energy Sources
natenvir: Federal spending: Improving & Protecting Environment
natfare: Federal spending: Welfare
natheal: Federal spending: Improving & Protecting Nations Health
natmass: Federal spending: Mass Transportation
natpark: Federal spending: Parks and Recreation
natrace: Federal spending: Improving the Conditions of Blacks
natroad: Federal spending: Highways and Bridges
natsci: Federal spending: Supporting Scientific Research
natsoc: Federal spending: Social Security
natspac: Federal spending: Space Exploration Program
news: How Often Does Respondent Read Newspaper
obey: To Obey
obey2: Obedience Important in Children?
owngun: Have Gun in Home
partyid: Political Party Affiliation
partyid_3: Party Id: 3 Categories
polviews: Ideological Self-Placement
popular: Important for Child: To Be Well Liked or Popular
pornlaw: Feelings About Pornography Laws
pornlaw2: Pornography opinion
postlife: Belief in Life After Death
pray: How Often Does Respondent Pray
premarsx: Sex Before Marriage
pres08: Vote Obama or Mccain
racdif1: Differences Due to Discrimination
racdif2: Differences Due to Inborn Disability
racdif3: Differences Due to Lack of Education
racdif4: Differences Due to Lack of Will
race: Race of Respondent
race_2: Race: Black / White
racial_liberal3: Racial Liberalism
reborn_r: Born Again?
region: Region of Interview
relig: Respondent's Religious Preference
relig2: Respondent's Religious Preference, limited to Catholic and Protestant
reliten: Strength of Affiliation
reliten2: Strong Religious Affiliation
rincom06: Respondent Income
rincom06_5: Respondent Income: 5 Categories
savesoul_r: Tried to Convince Others of Jesus?
science_quiz: Number Correct on Science Quiz
science_quiz.f: Number Correct on Science Quiz, stored as factor
sex: Respondent's Sex
sibs: Number of Brothers and Sisters
size: Size of Place in 1000s
social_connect: Social Connectedness
social_cons3: Social Conservatism
social_trust: Social Trust (Numeric Scale)
south: Respondent from South?
spanking: Favor Spanking to Discipline Child?
spanking2: Approve of spanking
spend3: Econ Liberalism
spkath: Allow Speaker in Your Community: Anti-Religionist
spkcom: Allow Speaker in Your Community: Communist
spkhomo: Allow Speaker in Your Community: Homosexual
spkmil: Allow Speaker in Your Community: Militarist
spkmslm: Allow Speaker in Your Community: Muslim Clergymen Preaching Hatred
spkrac: Allow Speaker in Your Community: Allow Racist to Speak
teensex: Sex Before Marriage – Teens 14-16
thnkself: Important for Child: To Think For One's Self
tolerance: Tolerance Scale
tolerance4: Tolerance Scale (Binned)
tvhours: Hours Per Day Watching TV
tvhours5: Hours per day
union: Does Respondent or Spouse Belong to Union
uscitzn: Is Respondent US Citizen
vetyears: Years in Armed Forces
vote08_coded: Did Respondent Vote in 2008 Election
voted08: Did Respondent Vote in 2008?
white_traits: White Stereotypes
wordsum: Number Words Correct in Vocabulary Test
workhard: To Work Hard
wrkgvt: Respondent Work for Government or Private Employee
wrkslf: Respondent Self-Emp or Works For Somebody
wrkstat: Labor Force Status
wrkwayup: Irish, Italian, Jewish and other Should Overcome Prejudice Without Favors
wtss: Weight Variable
wtssall: Weight Variable (same as wtss)
xmarsex: Sex With Person Other Than Spouse
year: GSS Year For This Respondent
zodiac: Respondent's Astrological Sign

Source

2012 General Social Survey. See Appendix Table A.1 of printed textbook for further information

GSS design dataset for R Companion to Essentials of Political Analysis, Second Edition

Description

The General Social Survey polls individuals about their attitudes and beliefs. This design dataset is used to demonstrate application of certain R functions to political analysis. See gss dataset documentation for variable names and descriptions.

Usage

gssD
gssD

Format

A design dataset version of the gss dataset used for certain weighted analyses. The variables element has 1974 observations of 221 variables.

Source

2012 General Social Survey. See Appendix Table A.1 of printed textbook for further information

Controlled Mean Comparison Table

Description

Produces a controlled mean comparison table. Rows defined by values of independent variable and columns defines by values of the control variable.

Usage

imeansC(function1 = NULL, function2 = NULL, data, digits = 2)
imeansC(function1 = NULL, function2 = NULL, data, digits = 2)

Arguments

`function1`	A function identifying the dependent variable in the form ~ depvar
`function2`	A function specifying the independent and control variables in the form ~ indepvar + controlvar
`data`	A design dataset (like gssD, nesD, statesD, or worldD)
`digits`	Number of digits to report after decimal place, optional (default = 2).

Value

A controlled mean comparison table (an "ftable" class object)

Examples

   library(poliscidata)
   
   imeansC(function1 = ~ft_dem, function2 = ~gender + married, data=nesD)
   
   imeansC(~ft_dem, ~gender + married, nesD)
library(poliscidata)
   
   imeansC(function1 = ~ft_dem, function2 = ~gender + married, data=nesD)
   
   imeansC(~ft_dem, ~gender + married, nesD)

Calculates predicted probability for a given logged odds value

Description

This function calculates predicted probability for a given logged odds value, often useful for plotting or reporting predicted probabilities.

Usage

inverse.logit(logged_odds)
inverse.logit(logged_odds)

Arguments

logged_odds

A numeric value, or vector of numeric values.

Value

Returns predicted probability corresponding the the logged odds value, a numeric value between 0 and 1.

Examples

   inverse.logit(0)
   
   inverse.logit(-5:5)
inverse.logit(0)
   
   inverse.logit(-5:5)

Interaction plot

Description

Interaction plot uses brkdn.plot in plotrix package and svyby function from survey package. Warnings suppressed so the function creates plot without generating intermediate results used to create plot.

Usage

iplotC(function1 = NULL, function2 = NULL, data, function3 = NULL, ...)
iplotC(function1 = NULL, function2 = NULL, data, function3 = NULL, ...)

Arguments

`function1`	A function in the form ~depvar
`function2`	A function. Here indepvar is typed before controlvar: ~indepvar + controlvar
`data`	Design dataset (e.g. nesD, gssD, statesD, or worldD)
`function3`	A function. Here indepvar is typed after controlvar: ~controlvar + indepvar
`...`	Further arguments to be passed to `brkdn.plot` function (plotrix package)

Value

No value returned

Examples

   library(poliscidata)
   
   iplotC(function1 = ~ ft_dem, function2 = ~ gender + married, 
          data = nesD, function3 = ft_dem ~ married + gender)
   
   iplotC(~ft_dem, ~gender+married, nesD, ft_dem~married+gender,
          xlab="Gender", ylab="Democratic Party Rating", 
          main="Democratic Party Rating by Gender and Marital Status")
library(poliscidata)
   
   iplotC(function1 = ~ ft_dem, function2 = ~ gender + married, 
          data = nesD, function3 = ft_dem ~ married + gender)
   
   iplotC(~ft_dem, ~gender+married, nesD, ft_dem~married+gender,
          xlab="Gender", ylab="Democratic Party Rating", 
          main="Democratic Party Rating by Gender and Marital Status")

Displays line types for R plots

Description

Displays line types for R plots. No values supplied to function.

Usage

lineType()
lineType()

Value

No value returned

Examples

  lineType()
lineType()

Logistic regression model statistics

Description

Logistic regression model statistics

Usage

logregR2(model, digits = 3)
logregR2(model, digits = 3)

Arguments

`model`	An estimated logistic regression model
`digits`	Number of digits to be displayed after decimal points

Value

Returns list of statistics about model (a "LogRegR2" class object)

Examples

   library(poliscidata)
   obama_state_model <- glm(obama_win12 ~ secularism + gunlaw_rank, data=states, family=binomial)
   summary(obama_state_model)
   logregR2(obama_state_model)
   
   obama_vote_model <- svyglm(obama_vote ~ ft_dem, design=nesD, family="quasibinomial")
   summary(obama_vote_model)
   logregR2(obama_vote_model)
library(poliscidata)
   obama_state_model <- glm(obama_win12 ~ secularism + gunlaw_rank, data=states, family=binomial)
   summary(obama_state_model)
   logregR2(obama_state_model)
   
   obama_vote_model <- svyglm(obama_vote ~ ft_dem, design=nesD, family="quasibinomial")
   summary(obama_vote_model)
   logregR2(obama_vote_model)

NES dataset for R Companion to Essentials of Political Analysis, Second Edition

Description

The American National Election Survey polls individuals about their political beliefs and behavior. This dataset is used to demonstrate application of R to political analysis. See book Appendix for variable names and descriptions.

Usage

nes
nes

Format

A data frame with 5916 rows and 399 variables.

abort_scale: Anti-abortion Scale
abort4: Abortion Opinion: Self-Placement, 4 Categories
abortpre_4point: Abortion Opinion: Self-Placement, 4 Categories
aidblack_self: Support for Government assistance to blacks scale, 7 point scale
auth_consid: Child trait more important: considerate or well-behaved
auth_cur: Child trait more important: curiosity or good manners
auth_ind: Child trait more important: independence or respect
auth_obed: Child trait more important: obedience or self-reliance
authoritarianism: Authoritarianism (4 point scale based on child trait questions)
black: Is Respondent Black?
budget_deficit_x: Favor reducing the Federal budget deficit, 7 point scale
caseid: Case ID
casistart_iwrset4: Does Respondent have a dog (Interview set-up test)
casistartpo_iwrset4: Does Respondent have a dog (Interview set-up test)
cog_opin_x: Number of opinions Respondent has compared to average person
congapp_job_x: Approval of Congress
congapp_jobst: Strength of approve/disapprove Congress handling its job
conservatism: ftgr_cons minus ftgr_liberals
cses_closepty: Close to any political party?
cses_contct: Campaign mobilization: institutional contact
cses_email: Campaign mobilization: institutional contact - email
cses_ftf: Campaign mobilization: institutional contact - in person
cses_gotv: Respondent contacted by party/candidate?
cses_govtact: Support for government action income inequality (5 point scale)
cses_govtact_3: Government action on income inequality (3 point scale)
cses_mail: Campaign mobilization: institutional contact - by mail
cses_mobph: Campaign mobilization: sign up online information or alerts
cses_perseml: Campaign mobilization: personal contact - email
cses_persftf: Campaign mobilization: personal contact - in person
cses_persmail: Campaign mobilization: personal contact - by mail
cses_persph: Campaign mobilization: personal contact - by phone
cses_perstxt: Campaign mobilization: personal contact - text message
cses_persuade: Campaign mobilization: personal contact
cses_persweb: Campaign mobilization: personal contact - social network
cses_phone: Campaign mobilization: institutional contact - by phone
cses_poliinffour: Political information - Secretary of the U.N.
cses_poliinfone: Political information - Secretary of the Treasury
cses_poliinfthree: Political information - party 2nd in House seats won
cses_polinf_x: Pol info scale
cses_polinftwo: Political information - unemployment rate
cses_polinftwo_date: Political information - date used for date of unemployment rate
cses_polinftwo_rate: Political information - number used for unemployment rate
cses_spending: Econ conservatism (numeric scale)
deathpen: Death Penalty Opinion
defsppr_self: Support for defense spending, 7 point scale
dem: Party identification: Does Respondent self-identify as Democrat? (coded 0/1)
dem_age_group_r: Demographic: Age Groups
dem_age3: Demographic: Age group
dem_age6: Demographic: Six Age Groups
dem_agegrp_iwdate: Demographic: Respondent age on interview date (age group)
dem_educ3: Demographic: Education
dem_edugroup: Demographic: Respondent level of highest education
dem_hisp: Demographic: Is Respondent Spanish, Hispanic, or Latino
dem_marital: Demographic: Marital status
dem_parents: Demographic: Native status of parents
dem_racecps_black: Demographic: Race self-identification: mention Black
dem_racecps_racedkrf: Demographic: Race self-identification with don't know or refused to say
dem_racecps_white: Demographic: Race self-identification: mention White
dem_raceeth: Demographic: Respondent race and ethnicity group
dem_raceeth2: Demographic: White/Black
dem_raceeth4: Demographic: Respondent race and ethnicity group
dem_unionhh: Demographic: Anyone in household belong to labor union
dem_veteran: Demographic: Respondent ever served on active duty in Armed Forces
dem2_numchild: Demographic: Total Number of children in household
dem3_ownhome: Demographic: Does Respondent family own/rent home
dem3_yearscomm: Demographic: How many years has Respondent lived in this community?
dhs_appterr_x: Homeland security: Approve/disapprove of efforts to reduce terrorism
dhs_attack: Homeland security: Likely terrorist attack kill 100/more in next year?
dhs_threat_x: Homeland security: Is fed. gov't a threat to rights and freedoms? (numeric scale)
dhs_threat3: Homeland security: Is fed. gov't a threat to rights and freedoms?
dhs_torture_x: Homeland security: Favor/Oppose torture for suspected terrorists
dhsinvolv_board: Civic engagement: Has Respondent in past 4 years: attended city/school board meeting
dhsinvolv_call: Civic engagement: Has Respondent in past 4 years: called radio/TV about political issue
dhsinvolv_contact1: Civic engagement: Contact U.S. Representative or Senator
dhsinvolv_letter: Civic engagement: written a letter to newspaper/magazine about political issue
dhsinvolv_march: Civic engagement: Has Respondent joined a protest march
dhsinvolv_message: Civic engagement: sent Facebook/Twitter message about political issue
dhsinvolv_netpetition: Civic engagement: Has Respondent in past 4 years: sign internet petition
dhsinvolv_org: Civic engagement: Has Respondent in past 4 years: gave money to social/political organization
dhsinvolv_petition: Civic engagement: Has Respondent signed paper petition
dhsinvolv_relig: Civic engagement: Has Respondent in past 4 years: given money to religious organization
discrim_blacks: Discrimination: Amount against Blacks
discrim_blacks_r: Discrimination: Against Blacks? (yes/no)
discrim_gays: Discrimination: Amount against Gays and Lesbians?
discrim_gays_r: Discrimination: Against gays? (yes/no)
discrim_hispanics: Discrimination: Amount against Hispanics
discrim_hispanics_r: Discrimination: Against Hispanics? (yes/no)
discrim_scale: Discrimination: How much discrimination against blacks, gays, Hispanics, women? (Sum of yes answers)
discrim_self: Discrimination: How much discrimination faced personally?
discrim_whites: Discrimination: Amount against Whites
discrim_women: Discrimination: Amount against Women
discrim_women_r: Discrimination: Against women? (yes/no)
discuss_disc: Ever discuss politics with family or friends
discuss_discpstwk: Days in past week discussed politics
ecblame_fmpr: Economy: How much is former President to blame for poor economy?
ecblame_pres: Economy: How much is President to blame for poor economy?
econ_ecnext_x: Economy: U.S. economy better or worse 1 year from now
econ_ecnextamt: Economy: How much better/worse next 12 months
econ_ecnow: Economy: Currently good or bad
econ_ecpast: Economy: Better/worse in last year
econ_ecpast_x: Economy: Better or worse than 1 year ago
econ_ecpastamt: Economy: How much better/worse in last year
econ_unlast: Economy: How much unemployment better/worse in last year
econ_unnext: Economy: More/less unemployment in next year
econ_unpast: Economy: Unemployment better/worse in last year
econ_unpast_x: Economy: Unemployment better/worse than 1 year ago
econcand_dwin: Economy: Better/worse if Democratic Presidential candidate wins
econcand_rwin: Economy: Better/worse if Republican Presidential candidate wins
ecperil_home: How do you pay for your home?
effic_carerev: Political efficacy: Public officials don't care what people think
effic_carestd: Political efficacy: Public officials don't care what people think
effic_complicrev: Political efficacy: Politics/government too complicated to understand
effic_complicstd: Political efficacy: Politics/government too complicated to understand
effic_external: Political efficacy: External political efficacy (numeric scale)
effic_external3: Political efficacy: External political efficacy (3 categories)
effic_internal: Political efficacy: Internal political efficacy (numeric scale)
effic_internal3: Political efficacy: Internal political efficacy (3 categories)
effic_sayrev: Political efficacy: Have no say about what government does
effic_saystd: Political efficacy: Have no say about what government does
effic_undrev: Political efficacy: Good understanding of political issues
effic_undstd: Political efficacy: Good understanding of political issues
efficpo_bothside: Political efficacy: How often see both disagreeing parties as right
egal_bigprob: Equality: It's a big problem that we don't give equal chance to succeed
egal_equal: Equality: Society should make sure everyone has equal opportunity
egal_fewerprobs: Equality: If people were treated more fairly would be fewer problems
egal_notbigprob: Equality: Not a big problem if some have more chance in life
egal_scale: Equality: Egalitarianism (numeric scale)
egal_scale_3: Equality: Egalitarianism: 3 categories
egal_toofar: Equality: We have gone too far pushing equal rights
egal_worryless: Equality: We'd be better off if worried less about equality
envir: Environment: Environment more important response (on envjob_3) as 0/100
envir_drill: Environment: Favor/oppose increased U.S. offshore drilling
envir_gwarm: Environment: Is global warming happening or not
envir_gwgood: Environment: Rising temperatures good or bad
envir_gwhow: Environment: Anthropogenic climate change
envir_nuke: Environment: Should US have more/fewer nuclear power plants
enviro.yes: Environment: Environment more important response (on envjob_3) as 0/100
envjob_3: Environment: Environment or jobs more important?
envjob_self: Environment: 7 point scale environment-jobs tradeoff
fairjob_opin_x: Opinion about government ensuring fair jobs for blacks
fedspend_child: Federal budget increase/decrease: child care
fedspend_childr: Federal budget increase/decrease: child care (rev. scale)
fedspend_crime: Federal budget increase/decrease: crime control
fedspend_crimer: Federal budget increase/decrease: crime control (rev. scale)
fedspend_enviro: Federal budget increase/decrease: protecting environment
fedspend_enviror: Federal budget increase/decrease: protecting environment (rev. scale)
fedspend_poor: Federal budget increase/decrease: aid to the poor
fedspend_poorr: Federal budget increase/decrease: aid to the poor (rev. scale)
fedspend_scale: Federal Spending Scale (numeric scale, sum of increase responses)
fedspend_schools: Federal budget increase/decrease: public schools
fedspend_schoolsr: Federal budget increase/decrease: public schools (rev. scale)
fedspend_scitech: Federal budget increase/decrease: science and technology
fedspend_scitechr: Federal budget increase/decrease: science and technology (rev. scale)
fedspend_ss: Federal budget increase/decrease: Social Security
fedspend_ssr: Federal budget increase/decrease: Social Security (rev. scale)
fedspend_welfare: Federal budget increase/decrease: welfare programs
fedspend_welfarer: Federal budget increase/decrease: welfare programs (rev. scale)
fem3: Feeling about feminists (recode of ftgr_feminists into 3 categories)
finance_finfam: Financial situation: Respondent living with how many family members
finance_finnext_x: Financial situation: Better or worse off 1 year from now
finance_finpast_x: Financial situation: Better or worse off than 1 year ago
ft_dem: Feeling Thermometer: Democratic Party
ft_dpc: Feeling Thermometer: Democratic Presidential candidate
ft_dvpc: Feeling Thermometer: Democratic Vice-Presidential candidate
ft_gwb: Feeling Thermometer: G.W. Bush
ft_hclinton: Feeling Thermometer: Hillary Clinton
ft_rep: Feeling Thermometer: Republican Party
ft_rpc: Feeling Thermometer: Republican Presidential candidate
ft_rvpc: Feeling Thermometer: Republican Vice-Pres candidate
ftcasi_asian: Feeling thermometer: Asian-Americans
ftcasi_black: Feeling thermometer: Blacks
ftcasi_hisp: Feeling thermometer: Hispanics
ftcasi_illegal: Feeling thermometer: Illegal Immigrants
ftcasi_white: Feeling thermometer: Whites
ftf_oversample: Was Respondent a 2012 Time Series Oversample Case?
ftgr_atheists: Feeling thermometer: Atheists
ftgr_bigbus: Feeling thermometer: Big Business
ftgr_catholics: Feeling thermometer: Catholics
ftgr_congress: Feeling thermometer: Congress
ftgr_cons: Feeling thermometer: Conservatives
ftgr_fedgov: Feeling thermometer: Federal Government
ftgr_fem3: Feeling thermometer: Feminists (3 categories)
ftgr_feminists: Feeling thermometer: Feminists
ftgr_gay: Feeling thermometer: Gay Men and Lesbians
ftgr_liberals: Feeling thermometer: Liberals
ftgr_middle: Feeling thermometer: Middle Class People
ftgr_military: Feeling thermometer: The Military
ftgr_mormons: Feeling thermometer: Mormons
ftgr_muslims: Feeling thermometer: Muslims
ftgr_poor: Feeling thermometer: Poor People
ftgr_rich: Feeling thermometer: Rich People
ftgr_tea: Feeling thermometer: Tea Party
ftgr_unions: Feeling thermometer: Labor Unions
ftgr_ussc: Feeling thermometer: The U.S. Supreme Court
ftgr_welfare: Feeling thermometer: People on Welfare
ftgr_working: Feeling thermometer: Working Class People
ftgr_xfund: Feeling thermometer: Christian Fundamentalists
ftgr_xian: Feeling thermometer: Christians
ftpo_dpcsp: Feeling thermometer: Spouse of Democratic Presidential candidate
ftpo_dvpc: Feeling thermometer: Democratic Vice Presidential candidate
ftpo_hdc: Feeling thermometer: House Democratic Candidate
ftpo_hoth: Feeling thermometer: House Independent/3rd-party Candidate
ftpo_hrc: Feeling thermometer: House Republican Candidate
ftpo_pres: Feeling thermometer: Democratic Presidential candidate
ftpo_roberts: Feeling thermometer: John Roberts
ftpo_rpc: Feeling thermometer: Republican Presidential candidate
ftpo_rpcsp: Feeling thermometer: Spouse of Republican Presidential candidate
ftpo_rvpc: Feeling thermometer: Republican Vice Presidential candidate
ftpo_sdc: Feeling thermometer: Senate Democratic Candidate
ftpo_senjr: Feeling thermometer: Jr. Senator in State Without Race
ftpo_sennot: Feeling thermometer: Non-running Senator in State W/Race
ftpo_sensr: Feeling thermometer: Sr. Senator in State Without Race
ftpo_soth: Feeling thermometer: Senate Independent/3rd-party Candidate
ftpo_src: Feeling thermometer: Senate Republican Candidate
gay_adopt: Gay rights: gayrt_adopt==1. Yes
gay_disc: Gay rights: gayrt_discstd_x==1. Approve strongly
gay_marry: Gay rights: Approve same-sex marriage?
gay_mil: Gay rights: gayrt_milstd_x==1. Feel strongly that homosexuals should be allowed to serve
gay_rights3: Gay rights: Gay Rights Support (3 categories)
gayrt_adopt: Gay rights: Should gay and lesbian couples be allowed to adopt?
gayrt_discrev_x: Gay rights: favor laws against gays/lesbians job discrimination (rev.)
gayrt_discstd_x: Gay rights: favor laws against gays/lesbians job discrimination
gayrt_marry: Gay rights: Respondent position on gay marriage
gayrt_milrev_x: Gay rights: allow gays/lesbians serve in US armed forces (reversed)
gayrt_milstd_x: Gay rights: allow gays/lesbians serve in US armed forces
gender: Respondent's Gender
govrole_scale: Pro-government scale (numeric scale)
guarpr_self: Should gov't guarantee a job and standard of living? (7 point scale)
gun_control: Gun control: Should federal gov't make it more difficult to buy a gun?
gun_control2: Gun control: Make it more difficult to buy a gun?
gun_importance: Gun control: Importance of gun access issue to R
gun_importance3: Gun control: How important is gun issue?
happ_lifesatisf: How satisfied is Respondent with life?
health_2010hcr_x: Health care: Support 2010 health care law
health_insured: Health care: Does Respondent have health insurance
health_self: Health care: Health of Respondent
health_smoke: Health care: Smoked Cigarettes
health_smokeamt: Health care: If smoked, how many now
hispanic: Is Respondent Hispanic?
hlthlaw_num: Health care: Health Care Law effect on number insured
hlthlaw_qual: Health care: Health Care Law effect on health care services
hseinc_approval: Congress: Approve or disapprove of House incumbent
hseinc_approval_x: Congress: House incumbent approval
hseinc_appstr: Congress: How much approve House incumbent
hseinc_disstr: Congress: How much disapprove House incumbent
hseinc_hinctouch: Congress: How good a job does House incumbent do in district
immig_checks: Immigration: Opinion on immigration status checks on suspects
immig_citizen: Immigration: Opinion on allowing citizenship to some illegal aliens
immig_policy: Immigration: U.S. government policy toward unauthorized immigrants
immigpo_jobs: Immigration: How likely immigration will take away jobs
immigpo_level: Immigration: What should immigration levels be
imports_limit: Favor or oppose limits on foreign imports
inc_incgroup_pre: Respondent's family income
incgroup_prepost: Respondent's family income
income5: Respondent's income quintile
indifference: Indifference scale
ineq_incgap_x: Income gap size compared to 20 years ago
ineqinc_ineqgb: Is increased income inequality in U.S. good?
ineqinc_ineqreduc: Does Respondent favor/oppose government reducing income inequality?
inspre_self: Health care: Should care be insured by government or by private medical insurance? (7 point scale)
involv_contact: Involvement in politics: Contact congress?
involv_message: Involvement in politics: post political message?
involv_numorgs_4: Involvement in politics: Number of group memberships
involv_org: Involvement in politics: Give money to political organization?
involv_petition: Involvement in politics: Sign net petition?
involv_voltr: Involvement in politics: Has Respondent done any volunteer work in past 12 months?
israel_support: Is U.S. too supportive of Israel or not supportive enough
knowl_housemaj: Political knowledge: Know party with most members in House?
knowl_senmaj: Political knowledge: Know party with most members in Senate?
libcon3: Respondent's Political Ideology (3 categories)
libcpo_self: Respondent's Political Ideology (7 point scale)
libcpre_ptyd: Ideological placement of Democrats (7 point scale)
libcpre_ptyr: Ideological placement of Republicans (7 point scale)
libcpre_rpc: Ideological placement of Republican Pres. Candidate (7 point scale)
libcpre_self: Respondent's Political Ideology (7 point scale)
libcpre_self_x: Respondent's Political Ideology (7 point scale)
link_black_scale: Linked fate: blacks
link_hisp_scale: Linked fate: Hispanics
link_oth_scale: Linked fate: other people
link_white_scale: Linked fate: whites
link_wom_scale: Linked fate: women
married: Demographic: Is Respondent married?
mobilpo_x: Campaign mobilization: Respondent contacted by Party, Candidates, GOTV (numeric scale)
mode: Mode of interview (face-to-face or internet)
modsex_disc: Sex discrimination: How much job discrimination against women
modsex_discamt: Sex discrimination: Discrimination against women
modsex_media_x: Sex discrimination: How much attention media should pay to discrimination against women
modsex_oppor_x: Sex discrimination: Opportunities compared for women and men
modsex_prob: Sex discrimination: Do women complaining about discrimination cause more problems
modsex_scale: Sex discrimination: Modern sexism
modsex_special: Sex discrimination: Do women demanding equality seek special favors
modsex_wommore: Sex discrimination: How much more opportunities do women have
mormon_xn: Mormon a Christian religion?
nesw: Sampling weights: Weight variable
nesw_rnd: Sampling weights: Weight variable (rounded)
obama_therm: Obama Rating
obama_vote: Respondent vote for Obama?
orientn_knowgay: Sexual orientation of family and friends
orientn_rgay: Respondent's sexual orientation
own_dog: Does Respondent own a dog?
owngun_owngun: Does Respondent own a gun
patriot_amident: Patriotism: Important being American
patriot_flag: Patriotism: Emotion seeing flag fly
patriot_love: Patriotism: Love of country
patriotism: Patriotism scale
penalty_dpenstr: Strength Respondent favors/opposes death penalty
penalty_favdpen: Respondent favor/oppose death penalty
penalty_favopp_x: Favor death penalty?
pid_3: Party Identification, 3 categories
pid_x: Party Identification, 7 categories
polknow_combined: Political knowledge: Number political facts correct
polknow3: Political knowledge, 3 categories
postvote_presvt: Did Respondent vote for President
postvote_presvtwho: For whom did Respondent vote for President
postvote_rvote: Did Respondent vote in the November general election
postvote_votehs: Did Respondent vote for U.S. House of Representatives
pot_legal: Should marijuana be legal?
pot_legal3: Legalize marijuana?
preknow_leastsp: Political knowledge: Program that federal gov't spends the least on
preknow_medicare: Political knowledge: What is Medicare
preknow_prestimes: Political knowledge: Number of times president can be elected
preknow_senterm: Political knowledge: Years Senator Elected
preknow_sizedef: Political knowledge: Size of federal deficit
preknow3: Political knowledge, 3 categories
pres_econ: Presidential approval: Handling of economy (Recode of presapp_econ)
pres_vote12: Respondent's vote in 2012 presidential election
presapp_econ_x: Presidential approval: Handling of economy
presapp_foreign: Presidential approval: Handling of foreign relations
presapp_foreign_x: Presidential approval: Handling of foreign relations
presapp_health_x: Presidential approval: Handling of health care
presapp_job_x: Presidential approval: Handling of job
presapp_scale: Presidential approval scale
presapp_war_x: Presidential approval: Handling of war in Afghanistan
presvote2012_2: Respondent's vote in 2012 presidential election
presvote2012_x: Respondent's vote in 2012 presidential election
preswin_care: Care who wins Presidential Election
preswin_dutychoice_x: Does Respondent consider voting as duty/choice
prevote_primv: Did Respondent vote in the Presidential primary or caucus
prevote_primvwho: Which candidate did Respondent vote for in Pres. primary or caucus
prochoice_scale: Abortion: Pro-choice Scale
relig_4cat: Religion: Catholic, other Christian, other, or not religious?
relig_attend: Religion: Attend services
relig_attend3: Religion: Attend services
relig_bornagn: Religion: Does Christian Respondent consider self born-again?
relig_guide: Religion: Provides guidance in day-to-day living
relig_imp: Religion: Important to Respondent?
relig_imp2: Religion: Important to Respondent?
relig_import: Religion: Important part of Respondent's life
relig_pray: Religion: How often does Respondent pray
relig_wordgod: Religion: Is Bible word of God or men
resent_deserve: Black community: Agree/disagree blacks have gotten less than deserve
resent_racial_scale: Black community: Racial conservatism scale
resent_slavery: Black community: Agree/disagree past slavery make life more difficult
resent_try: Black community: Agree/disagree blacks must try harder to get ahead
resent_workway: Black community: Agree/disagree that blacks should work way up without special favors
rvote2012_x: Did Respondent vote in November general election?
sample_district: Respondent's Congressional district (in 113th U.S. Congress)
sample_ftfpsu: Sample strata: Primary sampling unit for face-to-face cases
sample_state: State of Respondent address
science_use: How often should gov't use scientific methods to solve problems?
scourt_elim_x: Should the Supreme Court be done away with?
scourt_remove_x: Should it be possible to remove Supreme Court justices?
south: Respondent from South?
spsrvpr_ssself: Support for government services/spending (7 point scale)
strata_ftf: Sample strata for face-to-face sample component
strata_full: Sample strata for full sample
tarp_favopp_x: Favor the TARP program?
tea_supp_x: Tea Party support
trad_adjust: Traditional values: Agree/disagree world is changing we should adjust
trad_famval: Traditional values: Agree/disagree that more emphasis needed on traditional family values
trad_lifestyle: Traditional values: Agree/disagree are newer lifestyles are breaking down society
trad_tolerant: Traditional values: Agree/disagree that one should be more tolerant of other moral standards
trad_values_scale: Traditional values: Moral traditionalism scale
trust_social: Trust: How often can people be trusted?
trustgov_bigintrst: Trust: Is government run by a few big interests or for benefit of all?
trustgov_corrpt: Trust: How many in government are corrupt?
trustgov_trustgrev: Trust: How often trust gov't in Wash to do what is right? (reversed)
trustgov_trustgstd: Trust: How often trust government in Wash to do what is right?
trustgov_waste: Trust: Does government waste much tax money?
trustgvpo_crook: Trust: How many in government are crooked?
usworld_stay: International relations: Country better off if we just stayed home
usworld_stronger: International relations: During last year, U.S. position in world is weaker/stronger/same?
version: ANES 2012 Time Series Release Version
voted2008: Did Respondent vote for President in 2008? (Recode of interest_voted2008)
voted2012: Did Respondent vote in 2012?
voter_type: Voter type (non, new, voter)
weight_ftf: Post-stratified weight for face-to-face cases, preliminary
weight_full: Post-stratified weight for full sample, preliminary release
weight_web: Post-stratified weight for web cases, preliminary release
white: Is Respondent white?
wiretap_warrant: Wiretaps: Favor or oppose authority to wiretap terrorism suspects?
wiretappo_toofar: Wiretaps: Has government power gone too far?
women_bond_x: Working women: Harder to establish bond with child?
women_role: Working women: Women's role (numeric scale)
women_role_2: Working women: Women's role at home or work?
women_works_x: Working women: Better if man works and woman takes care of home and family?
wpres_gdbd_x: How good/bad to have woman president in next 20 years?
wt: Sampling weight
year: ANES year

Source

2012 American National Election Survey. See Appendix Table A.2 of printed textbook for further information

NES design dataset for R Companion to Essentials of Political Analysis, Second Edition

Description

The American National Election Survey polls individuals about their political beliefs and behavior. This design dataset is used to demonstrate application of certain R functions to political analysis. See nes dataset documentation for variable names and descriptions.

Usage

nesD
nesD

Format

A design dataset version of the nes dataset used for certain weighted analyses. The variables element has 5916 observations of 399 variables.

Source

2012 American National Election Survey. See Appendix Table A.2 of printed textbook for further information

Translate logistic regression coefficients into odds ratios

Description

Generates odds-ratios based on logistic regression model coefficients

Usage

orci(model, digits = 3)
orci(model, digits = 3)

Arguments

`model`	An estimated logistic regression model
`digits`	Number of digits after decimal to display

Value

Returns odds rations and confidence intervals in columns (a matrix class object)

Examples

   library(poliscidata)
   obama_state_model <- glm(obama_win12 ~ secularism + gunlaw_rank, data=states, family=binomial)
   summary(obama_state_model)
   orci(obama_state_model)
   
   obama_vote_model <- svyglm(obama_vote ~ ft_dem, design=nesD, family="quasibinomial")
   summary(obama_vote_model)
   orci(obama_vote_model)
library(poliscidata)
   obama_state_model <- glm(obama_win12 ~ secularism + gunlaw_rank, data=states, family=binomial)
   summary(obama_state_model)
   orci(obama_state_model)
   
   obama_vote_model <- svyglm(obama_vote ~ ft_dem, design=nesD, family="quasibinomial")
   summary(obama_vote_model)
   orci(obama_vote_model)

Comparing Logistic Regression Models with Chi-Squared Test

Description

Comparing Logistic Regression Models with Chi-Squared Test

Usage

pchisqC(reduced, full, digits = 3)
pchisqC(reduced, full, digits = 3)

Arguments

`reduced`	The reduced logisitic regression model as an object. This is model with fewer independent variables.
`full`	The full logisitic regression model as an object. This is model with more independent variables.
`digits`	The number of digits to display after decimal point, default is 3.

Value

The chi-squared statistic, df, and p-value as a vector of numbers to test null hypothesis that full model no better than reduced model.

Examples

   library(poliscidata)
   
   obama_vote_model_reduced <- svyglm(obama_vote ~ ft_dem + white, design=nesD, 
                                      family="quasibinomial")
   obama_vote_model_full <- svyglm(obama_vote ~ ft_dem + white + (owngun_owngun=="1. Yes"), 
                                   design=nesD, family="quasibinomial")
   pchisqC(obama_vote_model_reduced, obama_vote_model_full)
library(poliscidata)
   
   obama_vote_model_reduced <- svyglm(obama_vote ~ ft_dem + white, design=nesD, 
                                      family="quasibinomial")
   obama_vote_model_full <- svyglm(obama_vote ~ ft_dem + white + (owngun_owngun=="1. Yes"), 
                                   design=nesD, family="quasibinomial")
   pchisqC(obama_vote_model_reduced, obama_vote_model_full)

Displays plotting characters available in R

Description

Displays plotting characters available in R. No values supplied to function.

Usage

plotChar()
plotChar()

Value

No return

Examples

  plotChar()
plotChar()

Plots mean comparison

Description

Plots the mean values of a dependent variable at different values of nominal or ordinal independent variable. Makes use of survey package's svy

Usage

plotmeansC(data, function1 = NULL, function2 = NULL, function3, w = 1, ...)
plotmeansC(data, function1 = NULL, function2 = NULL, function3, w = 1, ...)

Arguments

`data`	A dataset (e.g. gss, nes, states, or world) or design dataset (e.g. gssD, nesD, statesD, or worldD)
`function1`	A function in the form of ~ depvar
`function2`	A formula in the form of ~ indepvar
`function3`	A formula in the form of depvar ~ indepvar
`w`	Weights, in the form ~ weightvar (optional, not needed if you use a design dataset)
`...`	Additonal arguments passed to gplots package's `plotmeans` function

Value

No return

Examples

   library(poliscidata)
   
   plotmeansC(nesD, ~ft_hclinton, ~pid_x, ft_hclinton~pid_x, 
   xlab="Party Identification", ylab="Ratings of Hillary Clinton", 
   main="Ratings of Hillary Clinton by Party Identification")
   
   plotmeansC(nes,~envir,~pid_3,envir~pid_3,w=~wt,
   xlab="Party Identification",
   ylab="Percent Pro-Environment",
   main="Percentage Favoring Environment over Jobs,\n by Party ID")
   
library(poliscidata)
   
   plotmeansC(nesD, ~ft_hclinton, ~pid_x, ft_hclinton~pid_x, 
   xlab="Party Identification", ylab="Ratings of Hillary Clinton", 
   main="Ratings of Hillary Clinton by Party Identification")
   
   plotmeansC(nes,~envir,~pid_3,envir~pid_3,w=~wt,
   xlab="Party Identification",
   ylab="Percent Pro-Environment",
   main="Percentage Favoring Environment over Jobs,\n by Party ID")

Prints html-ready table to local working directory

Description

Prints html-ready table to local working directory. Makes use of xtable package's print.xtable function. See pp. 22 of An R Companion to Political Analysis for example and more information.

Usage

printC(objx)
printC(objx)

Arguments

objx

A table or data frame

Value

No return

Difference of Proportions Test

Description

Difference of proportions test with optional sample weights. Reports P-value of two-tailed significance test.

Usage

prop.testC(y, x, w = NULL, digits = 3)
prop.testC(y, x, w = NULL, digits = 3)

Arguments

`y`	Dependent variable, should be coded as 0 or 1.
`x`	Independent variable, should have only two unique values.
`w`	Weights, optional.
`digits`	Number of digits to report after decimal place, optional (default = 3).

Value

No return

Examples

   library(poliscidata)
   
   prop.testC(nes$dem, nes$gender, w=nes$nesw)
library(poliscidata)
   
   prop.testC(nes$dem, nes$gender, w=nes$nesw)

Prints string to console quickly

Description

Prints string to console quickly, but still scolls for visual effect

Usage

quickConsolePrint(linetoprint)
quickConsolePrint(linetoprint)

Arguments

linetoprint

Text to be printed to console

Value

No value returned

Sets contrasting color for text

Description

Sets color for text that effectively contrasts with the background color specified. Used by the Colors function.

Usage

SetTextContrastColor(color)
SetTextContrastColor(color)

Arguments

color

A color

Value

Returns either "black" or "white"

Prints string to console slowly

Description

Prints string to console slowly to make text more readable to the user. Used by welcome function.

Usage

slowConsolePrint(linetoprint, slow = 0.05)
slowConsolePrint(linetoprint, slow = 0.05)

Arguments

`linetoprint`	Text to be printed to console
`slow`	Time, in milliseconds, to wait between characters printed to console (default is .05).

Value

No value returned

Calculates Somer's D

Description

This function calculates the Somer's D measure of association statistic. This function makes use of the svytable function from the survey package.

Usage

somersD(formula, data)
somersD(formula, data)

Arguments

`formula`	A formula in the form ~ indepvar + depvar
`data`	A design dataset (e.g. gssD, nesD, statesD, or worldD)

Value

Return Somer's D measure of association statistic, a number between 0 and 1.

Examples

   library(poliscidata)
   
   somersD(~ dem_educ3 + envjob_3, nesD)
library(poliscidata)
   
   somersD(~ dem_educ3 + envjob_3, nesD)

Returns case-level information in order

Description

Returns case-level information in order specified by user.

Usage

sortC(data, id, by, descending = TRUE)
sortC(data, id, by, descending = TRUE)

Arguments

`data`	Dataset to be sorted.
`id`	A variable in the dataset (data) that identfies individual cases, typically the name of states, countries, etc.
`by`	Variable the dataset should be sorted by.
`descending`	Should the cases be sorted in descending order? By default, set to TRUE.

Value

A data frame of sorted observations.

Examples

   library(poliscidata)
   
   sortC(data=states, id=state, by=abortlaw10)
   
   sortC(data=states, id=state, by=abortlaw10, descending=FALSE)
library(poliscidata)
   
   sortC(data=states, id=state, by=abortlaw10)
   
   sortC(data=states, id=state, by=abortlaw10, descending=FALSE)

States dataset for R Companion to Essentials of Political Analysis, Second Edition

Description

A dataset with variables about the 50 states. This dataset is used to demonstrate application of R to political analysis. See book Appendix for variable names and descriptions.

Usage

states
states

Format

A data frame with 50 rows and 135 variables.

abort_rank3: Abortion restrictions (3 category ranking)
abort_rate05: Abortions per 1,000 women (2005)
abort_rate08: Number of abortions per 1,000 women aged 15-44 (2008)
abortion_rank12: 2012 Abortion rank (Americans United for Life)
abortlaw10: Number of restrictions on abortion (2010)
abortlaw3: Abortion restrictions (three tiers of number of restrictions)
adv_or_more: Percent of population with advanced degree or higher
alcohol: Alcohol consumption in gallons per capita (2007)
attend_pct: Percent frequently attend religious serviced (Pew)
ba_or_more: Percent of population with college degree or higher
battle04: Battleground state in 2004?
blkleg: Percent of state legislators who are black
blkpct04: Percent black (2004)
blkpct08: Percent black (2008)
blkpct10: Percent black (2010)
bush00: Percent voting for Bush in 2000
bush04: Percent voting for Bush in 2004
carfatal: Motor vehicle fatalities (per 100,000 pop)
carfatal07: Motor vehicle fatalities per 100,000 pop (2007)
cig_tax: Cigarette tax per pack (2007)
cig_tax_3: Cigarette tax per pack: 3 categories (2007)
cig_tax12: Cigarette tax per pack (2012)
cig_tax12_3: Cigarette tax per pack: 3 categories (2012)
cigarettes: Packs smoked bimonthly per adult (2003)
college: Percent of population with college or higher
conpct_m: Percent mass public Conservative
cons_hr06: Conservatism score, US House delegation (2006)
cons_hr09: Conservatism score, US House delegation (2009)
conserv_advantage: Conservative advantage, mass public (2012)
conserv_public: Percent mass public conservative (2013)
cook_index: Cook Index: Higher scores mean more Democratic
cook_index3: 3 quantiles of cook_index
defexpen: Federal defense expenditures per capita
dem_advantage: Democratic advantage, mass public (2012)
dem_hr09: Percent US House delegation Democratic (2009)
demhr11: Percent HR delegation Democratic (2011)
demnat06: Percent US House and Senate Democratic (2006)
dempct_m: Percent mass public Democratic
demstate06: Percent of state legislators who are Democrats (2006)
demstate09: Percent of state legislators who are Democrats (2009)
demstate13: Percent state legislature Democrats (2013)
density: Population density (2010)
division: Census division (9 different regions of country)
earmarks_pcap: Earmarks per capita (in dollars)
evm: State electoral vote: McCain (2008)
evo: State electoral vote: Obama (2008)
evo2012: Obama's Electoral College vote
evr2012: Romney's Electoral College vote
gay_policy: Billman's policy scale (4 ordinal categories)
gay_policy_con: Does state have 'most conservative' gay policies?
gay_policy2: RECODE of gay_policy (Billman's policy scale)
gay_support: Lax-Phillips opinion index
gay_support3: Gay rights: public support (3 categories)
gb_win00: Did Bush win electoral vote, 2000?
gb_win04: Did Bush win electoral vote, 2004?
gore00: Percent voting for Gore 2000
govt_worker: Percentage workforce government workers (2012)
gun_check: Background checks for gun purchases per 100,000 pop (2012)
gun_dealer: Gun dealers per 100,000 pop
gun_murder10: Gun murder rate (2010)
gun_rank_rev: Recode of gun_rank11 so higher number ranks = more gun restrictions
gun_rank11: Brady gun rank (2011)
gun_rank3: Recode of gun_rank11 (3 ordinal categories)
gun_scale11: Brady gun law scale (2011)
gunlaw_rank: Brady campaign rank (2008)
gunlaw_rank3_rev: Number of restrictions (2008)
gunlaw_scale: Brady campaign score (2008)
hispanic04: Percent Hispanic (2004)
hispanic08: Percent Hispanic (2008)
hispanic10: Percent Hispanic (2010)
hr_cons_rank11: Conservativism ranking of House of Representatives delegation (2011, American Conservative Union)
hr_conserv11: Conservativism rating of House of Representatives delegation (2011, American Conservative Union)
hr_lib_rank11: Liberalism ranking of House of Representatives delegation (2011, Americans for Democratic Action)
hr_liberal11: Liberalism rating of House of Representatives delegation (2011, Americans for Democratic Action)
hs_or_more: Percent population high school education or higher
indpct_m: Percent mass public Independent
kerry04: Percent voting for Kerry 2004
libpct_m: Percent mass public Liberal
mccain08: Percent voting for McCain 2008
modpct_m: Percent mass public Moderate
nader00: Percent voting for Nader 2000
obama_win08: Did Obama win electoral vote, 2008?
obama_win12: Did Obama win the state in 2012?
obama08: Percent voting for Obama 2008
obama2012: Obama vote share in 2012
over64: Percent population over age 64
permit: Percent public that would always permit abortion (2004 NES)
pop_18_24: Percent population aged 18-24 (2004)
pop_18_24_10: Percent population aged 18-24 (2010)
pop2000: State population, 2000
pop2010: State population, 2010
pop2010_hun_thou: State population, 2010 (in 100k)
popchng0010: State population, 2000-2012
popchngpct: State population percentage, 2000-2010
pot_policy: Marijuana laws
prcapinc: Per capita income
prochoice: Percent public pro-choice
prolife: Percent public pro-life
region: Census region (4 categories)
relig_cath: Percentage Catholic (2012)
relig_high: Percentage high religiosity (2012)
relig_import: Percent religion "A great deal of guidance"
relig_low: Percentage low religiosity (2012)
relig_prot: Percentage Protestant (2012)
religiosity: Religious observance-belief scale (Pew)
religiosity3: Religiosity (3 categories)
reppct_m: Percent mass public Republican
romney2012: Romney vote share in 2012
rtw: Right to work state?
secularism: Secularism scale (Pew)
secularism3: 3 quantiles of secularism
seniority_sen2: Does state have influential US Senator?
smokers12: Percentage of population who smoke
south: Southern state?
state: State name
stateid: Two letter postal abbreviation for state name
to_0004: Percentage point change in turnout from 2000 to 2004
to_0408: Percentage point change in turnout from 2004 to 2008
to_0812: Percentage point change in turnout from 2008 to 2012
trnout00: Turnout in 2000 presidential election
trnout04: Turnout in 2004 presidential election
unemploy: Unemployment rate (2004)
uninsured_pct: Percentage without health insurance (2012)
union04: Percent workers who are union members (2004)
union07: Percent workers who are union members (2007)
union10: Percent workforce unionized (2010)
urban: Percent urban population (2000)
vep00_turnout: Percent turnout of voting eligible population in 2000
vep04_turnout: Percent turnout of voting eligible population in 2004
vep08_turnout: Percent turnout of voting eligible population in 2008
vep12_turnout: Percent turnout of voting eligible population in 2012
womleg_2007: Percent of state legislators who are women (2007)
womleg_2010: Percent of state legislators who are women (2010)
womleg_2011: Percent of state legislators who are women (2011)
womleg_2015: Percent of state legislators who are women (2015)

Source

Data sources vary. See Appendix Table A.3 of printed textbook for further information.

States design dataset for R Companion to Essentials of Political Analysis, Second Edition

Description

This is a design dataset with variables about the 50 states. This design dataset is used to demonstrate application of certain R functions to political analysis. See states dataset documentation for variable names and descriptions.

Usage

statesD
statesD

Format

A design dataset version of the states dataset used for certain weighted analyses. The variables element has 50 observations of 135 variables.

Source

Sources vary. See Appendix Table A.3 of printed textbook for further information

Computes summary statistics

Description

Computes statistics for controlled mean comparison table. Used by imeansC function.

Usage

svybyC(formula1 = NULL, formula2 = NULL, data, ...)
svybyC(formula1 = NULL, formula2 = NULL, data, ...)

Arguments

`formula1`	A formula
`formula2`	A formula
`data`	Dataset
`...`	Further arguments to be passed to svyby function.

Value

A svyby-type object

Chi-Squared Statistic for Relationship Between Categorical Variables using Weighted Dataset

Description

This function reports chi-squared test statistic based on weighted dataset

Usage

svychisqC(formula, design)
svychisqC(formula, design)

Arguments

`formula`	Formula expressing the relationship between variables in the form ~ depvar + indepvar
`design`	Weighted design dataset (like gssD, nesD, statesD, or worldD)

Value

No return

Examples

   library(poliscidata)
   
   svychisqC(~ gay_rights3 + libcon3, nesD)
library(poliscidata)
   
   svychisqC(~ gay_rights3 + libcon3, nesD)

Produces summary statistics

Description

This function is called by somersD function.

Usage

tablesomersDC(x, dep = 2)
tablesomersDC(x, dep = 2)

Arguments

`x`	A svytable
`dep`	which dimension stands for the dependent variable (1 = ROWS, 2 = COLS), default is 2.

Value

No return

Function to Introduce Users to R Companion Environment

Description

Welcomes users to Companion Package to Political Analysis and provides basic information about using Companion functions and datasets.

Usage

welcome()
welcome()

Value

No value returned

World dataset for R Companion to Essentials of Political Analysis, Second Edition

Description

A dataset with variables about countries in the world. This dataset is used to demonstrate application of R to political analysis. See book Appendix for variable names and descriptions.

Usage

world
world

Format

A data frame with 167 rows and 103 variables.

arda: Country numerical code
colony: Colony of what country? (CIA)
confidence: Confidence in institutions scale (World Values Survey)
country: Country/territory name (title case)
country1: Country/territory name (title case), may be same as country
debt: Public debt as a percentage of GDP (CIA)
decent08: Democratic decentralization, 2008 (UN)
dem_economist: Full or Part Democracy (Economist, 2014)
dem_level4: Regime type (Economist 2014)
dem_other: Percentage of other democracies in region
dem_other5: Percentage of other democracies in region: 5 categories
dem_rank14: Democracy rank, lower scores more democratic (Economist 2014)
dem_score14: Democracy score, higher scores more democratic (Economist 2014)
democ: Is government a democracy? (Based on regime_type3)
democ.yes: Is government a democracy? Coded 0/100 (Based on regime_type3)
democ_regime: Is regime a democracy? (1990)
democ_regime08: Is government a democracy? (may be redundant)
democ11: Democracy score, 2011 (UN)
district_size3: Average # of members per district (World Values Survey)
dnpp_3: Effective number of parliamentary parties
durable: Number of years since the last regime transition (Polity)
effectiveness: Government effectiveness scale (Kaufmann 2002)
enpp3_democ: Effective number of parliamentary parties: 3 categories
enpp3_democ08: Effective number of parliamentary parties (World Values Survey)
eu: EU member state (yes/no)
fertility: Total fertility rate: Number children born per woman (CIA)
fhrate04_rev: Freedom House rating of democracy (reversed)
fhrate08_rev: Freedom House 1-7 scale reversed, rescaled 0-12
frac_eth: Ethnic factionalization (combined linguistic and racial) (Alesina et al 2003)
frac_eth2: Ethnic factionalization (combined linguistic and racial) (Binned)
frac_eth3: Level of ethnic fractionalization: 3 categories
free_business: Heritage Foundation rating: bus. freedom (2010)
free_corrupt: Heritage Foundation rating: corruption (2010)
free_finance: Heritage Foundation rating: financial freedom (2010)
free_fiscal: Heritage Foundation rating: fiscal freedom (2010)
free_govspend: Heritage Foundation rating: government spending (2010)
free_invest: Heritage Foundation rating: invest freedom (2010)
free_labor: Heritage Foundation rating: labor freedom (2010)
free_monetary: Heritage Foundation rating: monetary freedom (2010)
free_overall: Heritage Foundation rating: overall economic freedom (2010)
free_overall_4: 4 quantiles of free_overall
free_property: Heritage Foundation rating: property rights (2010)
free_trade: Heritage Foundation rating: free trade (2010)
gdp_10_thou: GDP per capita in 10K US$ (2002)
gdp_cap2: GDP per capita (US$): 2 categories (2002)
gdp_cap3: GDP per capita (US$): 3 categories (2002)
gdp08: GDP in billions in 2008 (World Bank)
gdpcap08_2: GDP per capita (US$) in 2008, 2 categories
gdpcap2_08: GDP per capita (US$) in 2008, 2 categories (may be redundant)
gdpcap3_08: GDP per capita (US$) in 2008 (Binned)
gdppcap08: GDP per capita in 2008 (World Bank)
gdppcap08_3: 3 quantiles of gdppcap08 (as numeric)
gender_equal3: Gender empowerment measure, 3 categories (World Values Survey)
gender_unequal: Gender Inequality Index value, 2008 (UN)
gender_unequal_rank: Gender Inequality Index rank, 2008 (UN)
gini04: Gini coefficient (UN 2004)
gini08: Gini coeff (UN 2008)
gini10: Income Gini coefficient, 2000-2010 (UN)
govregrel: Government regulation of religion index, 2008 (CIA)
hdi: Human development index (HDI) value, 2010 (UN)
hi_gdp: High GDP dummy
indy: Year of independence (CIA)
ipu_wom13_all: Percent Women in lower house of legislature, all countries, 2013 (Inter-Parliamentary Union)
lifeex_f: Life expectancy at birth among females (CIA)
lifeex_m: Life expectancy at birth among males (CIA)
lifeex_total: Life expectancy at birth, total population (CIA)
literacy: Literacy rate (CIA)
muslim: Is Muslim predominate religious group?
natcode: Name of country (lower case)
oecd: OECD member state (yes/no)
oil: Oil production, in barrels per day (CIA)
pmat12_3: Post-materialism, 3 categories (World Values Survey)
polity: Higher scores more democratic (Polity)
pop_0_14: Percentage of population age 0-14 (CIA)
pop_15_64: Percentage of population age 15-64 (CIA)
pop_65_older: Percent of population age 65 and older (CIA)
pop_age: Median age in years, 2010
pop_total: Total population in millions, 2010 (UN)
pop_urban: Percentage of the total population living in urban areas, 2010 (UN)
pr_sys: Proportional representation system? (Institute for Democracy and Electoral Assistance)
protact3: Protest activity (World Values Survey)
regime_type3: Regime type (Cheibub's Democracy Dictatorship dataset)
regionun: United Nations region
religoin: Largest religion by proportion (UN)
rich_democ: Rich democracy, interaction of Hi_gdp*democ_regime
sexratio: Sex ratio at birth (male births per 100 female births), 2010
spendeduc: Public expenditure on education as a percentage of GDP (UN)
spendhealth: Public expenditure on health as a percentage of GDP (UN)
spendmil: Public expenditure on the military as a percentage of GDP, 2008 (UN)
unions: Union density (www.ilo.org)
unnetgro: Percent growth in the number of Internet users, population based, 2000-2008 (UN)
unnetuse: Internet users per 100 people, 2008 (UN)
unpovnpl: Percentage of population below national poverty line, 2000-2008 (UN)
unremitp: Per capita remittance inflows in US dollars, 2008
unremitt: Remittance inflows as a percentage of GDP, 2008
vi_rel3: Percent saying religion very important, 3 categories
votevap00s: Turnout: most recent election in 2000s (Institute for Democracy and Electoral Assistance)
votevap90s: Turnout: elections in 1990s (Institute for Democracy and Electoral Assistance)
women05: Percent women in lower house of legislature, democracies only, 2005 (Inter-Parliamentary Union)
women09: Percent women in lower house of legislature, democracies only, 2009 (Inter-Parliamentary Union)
women13: Percent Women in lower house of legislature, democracies only, 2013 (Inter-Parliamentary Union)
womyear: Year women first enfranchised (Inter-Parliamentary Union)
womyear2: Women's suffrage (Inter-Parliamentary Union)

Source

Sources vary. See Appendix Table A.4 of printed textbook for further information.

World design dataset for R Companion to Essentials of Political Analysis, Second Edition

Description

This is a design dataset with variables about countries in the world. This dataset is used to demonstrate application of R to political analysis. See world dataset documentation for variable names and descriptions.

Usage

worldD
worldD

Format

A design dataset version of the world dataset used for certain weighted analyses. The variables element has 167 observations of 103 variables.

Source

Sources vary. See Appendix Table A.4 of printed textbook for further information

Weighted Box Plot

Description

The wtd.boxplot function is no longer being used by the poliscidata package. Please use the svyboxplot function instead. See svyhist documentation for details; also see pp. 67-69 of The R Companion to Political Analysis, 2nd Edition.

Usage

wtd.boxplot(...)
wtd.boxplot(...)

Arguments

...

Any arguments used will yield same warning message.

Value

Warning message only.

Find Median of Variable

Description

Takes in variable and finds median, works with sampling weights

Usage

wtd.median(x, weights = NULL)
wtd.median(x, weights = NULL)

Arguments

`x`	A variable
`weights`	Sampling weights of variable (optional)

Details

Makes use of the wtd.quantile function, part of the Hmisc package

Value

Returns the median value of the variable

Examples

   library(poliscidata)
   
   wtd.median(nes$budget_deficit_x, nes$wt)
library(poliscidata)
   
   wtd.median(nes$budget_deficit_x, nes$wt)

Find Mode of Variable

Description

Takes in variable and finds mode, works with sampling weights

Usage

wtd.mode(x, weights = NULL)
wtd.mode(x, weights = NULL)

Arguments

`x`	A variable
`weights`	Sampling weights of variable (optional)

Details

Makes use of the freq function, part of the descr package

Value

Returns the modal value of the variable

Examples

   library(poliscidata)
   
   wtd.mode(gss$zodiac, gss$wtss)
library(poliscidata)
   
   wtd.mode(gss$zodiac, gss$wtss)

Find Standard Deviation of Variable

Description

Takes in variable and calculates standard deviation, works with sampling weights.

Usage

wtd.sd(x, weights = NULL)
wtd.sd(x, weights = NULL)

Arguments

`x`	A variable (must be numeric), should be in dataset$var form.
`weights`	Sampling weights of variable (optional), should be in dataset$weightvar form.

Details

Makes use of the freq function, part of the descr package.

Value

Returns the standard deviation of the variable, a numeric value.

Examples

   library(poliscidata)
   
   wtd.sd(nes$polknow_combined, nes$wt)
library(poliscidata)
   
   wtd.sd(nes$polknow_combined, nes$wt)

Weighted T-Test

Description

This function conducts a weighted t-test

Usage

wtd.ttestC(f1, f2, data, digits = 3)
wtd.ttestC(f1, f2, data, digits = 3)

Arguments

`f1`	Function identifying interval-level dependent variable in the form ~ depvar
`f2`	A function that defines groups to be compared in the form ~ indepvar
`data`	A design dataset such as gssD, nesD, statesD, or worldD
`digits`	Number of digits to report after decimal place, optional (default = 3).

Value

No return

Examples

   library(poliscidata)
   
   wtd.ttestC(f1 = ~ ftgr_gay, f2 = ~ gender, data = nesD)
   
   wtd.ttestC(~ ft_rep, ~ gender, nesD)
library(poliscidata)
   
   wtd.ttestC(f1 = ~ ftgr_gay, f2 = ~ gender, data = nesD)
   
   wtd.ttestC(~ ft_rep, ~ gender, nesD)

Controlled cross tabulation analysis with optional weights

Description

Controlled cross tabulation analysis with optional weights

Usage

xtabC(function1, data, digits = 2)
xtabC(function1, data, digits = 2)

Arguments

`function1`	A function of the relationship to be analyzed expressed in the form ~ depvar + indepvar + controlvar
`data`	A design dataset (e.g. gssD, nesD, statesD, worldD)
`digits`	Number of digits to report after decimal place, optional (default = 2).

Value

A controlled cross tabulation as a multi-dimensional array.

Examples

   library(poliscidata)
   
   xtabC(~ divlaw2 + attend3 + kids, gssD)
library(poliscidata)
   
   xtabC(~ divlaw2 + attend3 + kids, gssD)

Cross tabulation Analysis

Description

Generates cross-tabulation of dependent and indendent variables, also creates a mosiac plot. Makes use of the crosstab function in the descr package.

Usage

xtp(
  data,
  y,
  x,
  w = NULL,
  ylab = NULL,
  xlab = NULL,
  main = NULL,
  digits = 2,
  chisq = FALSE
)
xtp(
  data,
  y,
  x,
  w = NULL,
  ylab = NULL,
  xlab = NULL,
  main = NULL,
  digits = 2,
  chisq = FALSE
)

Arguments

`data`	Dataset (like gss, nes, states, or world)
`y`	Dependent variable
`x`	Independent variable
`w`	Weights (optional)
`ylab`	Y-axis label (optional)
`xlab`	X-axis label (optional)
`main`	Main label for plot (optional)
`digits`	Number of digits to report after decimal place, optional (default = 2)
`chisq`	Do you want Chi-Squared test reported? (default is FALSE)

Value

A data frame of the cross tabulation results

Examples

   library(poliscidata)
   
   xtp(gss, grass, attend3, wtss)
library(poliscidata)
   
   xtp(gss, grass, attend3, wtss)

Cross tabulation Analysis with Chi-Squared Statistic

Description

This function makes use of the crosstab function from the descr package

Usage

xtp.chi2(data, y, x, w = NULL, digits = 1, prop.c = FALSE)
xtp.chi2(data, y, x, w = NULL, digits = 1, prop.c = FALSE)

Arguments

`data`	Dataset to be sorted
`y`	Dependent variable
`x`	Independent variable
`w`	Weights (optional)
`digits`	Number of digits to report after decimal place, optional (default = 1).
`prop.c`	Do you want column percentages reported in table? (default is FALSE)

Value

Returns a data frame of cross tabulation results

Examples

   library(poliscidata)
   
   xtp.chi2(gss, pornlaw, attend3, wtss)
library(poliscidata)
   
   xtp.chi2(gss, pornlaw, attend3, wtss)