Package: psych 2.4.6.26

William Revelle

psych:Procedures for Psychological, Psychometric, and Personality Research

A general purpose toolbox developed originally for personality, psychometric theory and experimental psychology. Functions are primarily for multivariate analysis and scale construction using factor analysis, principal component analysis, cluster analysis and reliability analysis, although others provide basic descriptive statistics. Item Response Theory is done using factor analysis of tetrachoric and polychoric correlations. Functions for analyzing data at multiple levels include within and between group statistics, including correlations and factor analysis. Validation and cross validation of scales developed using basic machine learning algorithms are provided, as are functions for simulating and testing particular item and test structures. Several functions serve as a useful front end for structural equation modeling. Graphical displays of path diagrams, including mediation models, factor analysis and structural equation models are created using basic graphics. Some of the functions are written to support a book on psychometric theory as well as publications in personality research. For more information, see the <https://personality-project.org/r/> web page.

Authors:William Revelle [aut, cre]

psych_2.4.6.26.tar.gz
psych_2.4.6.26.tar.gz(r-4.5-noble)psych_2.4.6.26.tar.gz(r-4.4-noble)
psych_2.4.6.26.tgz(r-4.4-emscripten)psych_2.4.6.26.tgz(r-4.3-emscripten)
psych.pdf |psych.html✨
psych/json (API)
NEWS

# Installpsych in R:
install.packages('psych',repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • Bechtoldt - Seven data sets showing a bifactor solution.
  • Bechtoldt.1 - Seven data sets showing a bifactor solution.
  • Bechtoldt.2 - Seven data sets showing a bifactor solution.
  • Chen - 12 variables created by Schmid and Leiman to show the Schmid-Leiman Transformation
  • Dwyer - 8 cognitive variables used by Dwyer for an example.
  • Garcia - Data from the sexism
  • Gleser - Example data from Gleser, Cronbach and Rajaratnam (1965) to show basic principles of generalizability theory.
  • Gorsuch - Example data set from Gorsuch (1997) for an example factor extension.
  • Harman.5 - Five data sets from Harman (1967). 9 cognitive variables from Holzinger and 8 emotional variables from Burt
  • Harman.8 - Five data sets from Harman (1967). 9 cognitive variables from Holzinger and 8 emotional variables from Burt
  • Harman.Burt - Five data sets from Harman (1967). 9 cognitive variables from Holzinger and 8 emotional variables from Burt
  • Harman.Holzinger - Five data sets from Harman (1967). 9 cognitive variables from Holzinger and 8 emotional variables from Burt
  • Harman.political - Five data sets from Harman (1967). 9 cognitive variables from Holzinger and 8 emotional variables from Burt
  • Holzinger - Seven data sets showing a bifactor solution.
  • Holzinger.9 - Seven data sets showing a bifactor solution.
  • Reise - Seven data sets showing a bifactor solution.
  • Schmid - 12 variables created by Schmid and Leiman to show the Schmid-Leiman Transformation
  • Tal.Or - Data set testing causal direction in presumed media influence
  • Tal_Or - Data set testing causal direction in presumed media influence
  • Thurstone - Seven data sets showing a bifactor solution.
  • Thurstone.33 - Seven data sets showing a bifactor solution.
  • Thurstone.33G - Seven data sets showing a bifactor solution.
  • Thurstone.9 - Seven data sets showing a bifactor solution.
  • Tucker - 9 Cognitive variables discussed by Tucker and Lewis
  • West - 12 variables created by Schmid and Leiman to show the Schmid-Leiman Transformation
  • bfi - 25 Personality items representing 5 factors
  • bfi.dictionary - 25 Personality items representing 5 factors
  • bfi.keys - 25 Personality items representing 5 factors
  • bock.table - Bock and Liberman (1970) data set of 1000 observations of the LSAT
  • cattell - 12 cognitive variables from Cattell
  • lsat6 - Bock and Liberman (1970) data set of 1000 observations of the LSAT
  • lsat7 - Bock and Liberman (1970) data set of 1000 observations of the LSAT
  • sat.act - 3 Measures of ability: SATV, SATQ, ACT
  • schmid.leiman - 12 variables created by Schmid and Leiman to show the Schmid-Leiman Transformation
  • small.msq - A small example data set taken from a larger data set
  • withinBetween - An example of the distinction between within group and between group correlations

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

472 exports 49 stars 8.74 score 4 dependencies 283 dependents 190.2k downloads

Last updated 8 days agofrom:26a808800d

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Dependencies:GPArotationlatticemnormtnlme

Scoring scales with psych

Rendered fromscoring.Rnwusingknitr::knitron Jun 28 2024.

Last update: 2024-06-28
Started: 2020-10-05

Readme and manuals

Help Manual

Help pageTopics
A package for personality, psychometric, and psychological researchpsych-package psych
Find two estimates of reliability: Cronbach's alpha and Guttman's Lambda 6.alpha alpha.ci alpha.scale alpha2r
Model comparison for regression, mediation, cluster and factor analysisanova.psych
Decision Theory measures of specificity, sensitivity, and d primeAUC auc Sensitivity Specificity
The Bass-Ackward factoring algorithm discussed by GoldbergbassAckward bassAckward.diagram
Seven data sets showing a bifactor solution.Bechtoldt Bechtoldt.1 Bechtoldt.2 Holzinger Holzinger.9 Reise Thurstone Thurstone.33 Thurstone.33G Thurstone.9
A bootstrap aggregation function for choosing most predictive unit weighted itemsbestItems bestScales BISCUIT biscuit BISCWIT biscwit
25 Personality items representing 5 factorsbfi bfi.dictionary bfi.keys
Draw pairs of bargraphs based on two groupsbi.bars
Find large correlation matrices by stitching together smaller ones found more rapidlybigCor
Draw biplots of factor or component scores by factor or component loadingsbiplot.psych
Create a block randomized structure for n independent variablesblock.random
Bock and Liberman (1970) data set of 1000 observations of the LSATbock bock.lsat bock.table lsat6 lsat7
12 cognitive variables from Cattell (1963)cattell
Apply four tests of circumplex versus simple structurecirc.tests
cluster Fit: fit of the cluster model to a correlation matrixcluster.fit
Find item by cluster correlations, corrected for overlap and reliabilitycluster.loadings
Plot factor/cluster loadings and assign items to clusters by their highest loading.cluster.plot fa.plot factor.plot
Convert a cluster vector (from e.g., kmeans) to a keys matrix suitable for scoring item clusters.cluster2keys
Find Cohen d and confidence intervalscd.validity cohen.d cohen.d.by cohen.d.ci d.ci d.robust d2CL d2OVL d2OVL2 d2r d2t d2U3 m2d m2t r2d t2d
Find Cohen's kappa and weighted kappa coefficients for correlation of two raterscohen.kappa wkappa
Convert base rates of two diagnoses and their comorbidity into phi, Yule, and tetrachoricscomorbidity
Matrix and profile congruences and distancescohen.profile congruence distance
Smooth a non-positive definite correlation matrix to make it positive definitecor.smooth cor.smoother
The sample size weighted correlation may be used in correlating aggregated datacor.wt
Convert correlations to distances (necessary to do multidimensional scaling of correlation data)cor2dist
Bootstrapped and normal confidence intervals for raw and composite correlationscor.ci corCi
Find a Full Information Maximum Likelihood (FIML) correlation or covariance matrix from a data matrix with missing datacorFiml
Create an image plot for a correlation or factor matrixcor.plot cor.plot.upperLowerCi corPlot corPlotUpperLowerCi
Find dis-attenuated correlations given correlations and reliabilitiescorrect.cor
Chi square tests of whether a single matrix is an identity matrix, or a pair of matrices are equal.cortest cortest.jennrich cortest.mat cortest.normal
Find the correlations, sample sizes, and probability values between elements of a matrix or data.frame.corr.p corr.test corTest
Bartlett's test that a correlation matrix is an identity matrixcortest.bartlett
Functions for analysis of circadian or diurnal datacircadian.cor circadian.F circadian.linear.cor circadian.mean circadian.phase circadian.reliability circadian.sd circadian.stats circular.cor circular.mean cosinor cosinor.period cosinor.plot
Simulate the C(ues) T(endency) A(ction) model of motivationcta cta.15
Create a 'violin plot' or density plot of the distribution of a set of variablesdensityBy violin violinBy
Basic descriptive statistics useful for psychometricsdescribe describeData describeFast
Basic summary statistics by groupdescribe.by describeBy
Helper functions for drawing path model diagramsdia.arrow dia.cone dia.curve dia.curved.arrow dia.ellipse dia.ellipse1 dia.rect dia.self dia.shape dia.triangle diagram multi.arrow multi.curved.arrow multi.rect multi.self
Draw a correlation ellipse and two normal curves to demonstrate tetrachoric correlationdraw.cor draw.tetra
Create dummy coded variablesdummy.code
8 cognitive variables used by Dwyer for an example.Dwyer
Convert eigen vectors and eigen values to the more normal (for psychologists) component loadingseigen.loadings
Plot data and 1 and 2 sigma correlation ellipsesellipses minkowski
Plot means and confidence intervalserror.bars error.bars.tab
Plot means and confidence intervals for multiple groupserror.bars.by
Plot x and y error barserror.crosses
Show a dot.chart with error bars for different groups or variableserror.dots
Two way plots of means, error bars, and sample sizeserrorCircles
Perform and Exploratory Structural Equation Model (ESEM) by using factor extension techniquescancorDiagram esem esem.diagram esemDiagram interbattery
Exploratory Factor analysis using MinRes (minimum residual) as well as EFA by Principal Axis, Weighted Least Squares or Maximum Likelihoodfa fa.pooled fa.sapa fac
Graph factor loading matricesextension.diagram fa.diagram fa.graph fa.rgraph het.diagram
Apply Dwyer's factor extension to find factor loadings for extended variablesfa.extend fa.extension faReg faRegression
A set of functions for factorial and empirical scale constructionfa.lookup item.lookup itemSort keys.lookup lmCorLookup lookup lookupFromKeys lookupItems
Multi level (hierarchical) factor analysisfa.multi fa.multi.diagram
Scree plots of data or correlation matrix compared to random ``parallel" matricesfa.parallel fa.parallel.poly paSelect plot.poly.parallel
Deprecated Exploratory Factor analysis functions. Please use fafa.poly factor.minres factor.pa factor.wls
A first approximation to Random Effects Exploratory Factor Analysisfa.random
Sort factor analysis or principal components analysis loadingsfa.organize fa.sort
Correlations between two factor analysis solutionsfaCor
Coefficient of factor congruencefa.congruence factor.congruence
How well does the factor model fit a correlation matrix. Part of the VSS packagefactor.fit
Find R = F F' + U2 is the basic factor modelfactor.model
R* = R- F F'factor.residuals
``Hand" rotate a factor loading matrixfactor.rotate
Various ways to estimate factor scores for the factor analysis modelfactor.scores
Find various goodness of fit statistics for factor analysis and principal componentsfa.stats factor.stats
Extract cluster definitions from factor loadingsfactor2cluster
Multiple rotations of factor loadings to find local minimafaRotations
Transformations of r, d, and t including Fisher r to z and z to r and confidence intervalschi2r cor2cov fisherz fisherz2r g2r r.con r2c r2chi r2p r2t t2r
Parse and exten formula input from a model and return the DV, IV, and associated terms.fparse
Data from the sexism (protest) study of Garcia, Schmitt, Branscome, and Ellemers (2010)Garcia GSBE protest
Find the geometric mean of a vector or columns of a data.frame.geometric.mean
Find the greatest lower bound to reliability.glb.algebraic
Example data from Gleser, Cronbach and Rajaratnam (1965) to show basic principles of generalizability theory.Gleser
Example data set from Gorsuch (1997) for an example factor extension.Gorsuch
Five data sets from Harman (1967). 9 cognitive variables from Holzinger and 8 emotional variables from BurtHarman Harman.5 Harman.8 Harman.Burt Harman.Holzinger Harman.political
Find the harmonic mean of a vector, matrix, or columns of a data.frameharmonic.mean
Combine calls to head and tailheadTail headtail quickView topBottom
Intraclass Correlations (ICC1, ICC2, ICC3 from Shrout and Fleiss)ICC
iclust: Item Cluster Analysis - Hierarchical cluster analysis using psychometric principlesICLUST iclust
Function to form hierarchical cluster analysis of itemsICLUST.cluster
Draw an ICLUST hierarchical cluster structure diagramICLUST.diagram iclust.diagram
create control code for ICLUST graphical outputICLUST.graph iclust.graph
Draw an ICLUST graph using the Rgraphviz packageICLUST.rgraph
Sort items by absolute size of cluster loadingsICLUST.sort iclust.sort
Find the interpolated sample median, quartiles, or specific quantiles for a vector, matrix, or data frameinterp.boxplot interp.median interp.q interp.qplot.by interp.quantiles interp.quart interp.quartiles interp.values
Item Response Theory estimate of theta (ability) using a Rasch (like) modelirt.0p irt.1p irt.2p irt.person.rasch
Item Response Analysis by Exploratory Factor Analysis of tetrachoric/polychoric correlationsfa2irt irt.fa irt.select
Simple function to estimate item difficulties using IRT conceptsirt.discrim irt.item.diff.rasch
Plot probability of multiple choice responses as a function of a latent traitirt.responses
Apply the Kaiser normalization when rotating factorskaiser
Find the Kaiser, Meyer, Olkin Measure of Sampling AdequacyKMO
Multiple Regression, Canonical and Set Correlation from matrix or raw inputcrossValidation crossValidationBoot lmCor lmCor.diagram lmDiagram mat.regress matPlot matReg set.cor setCor
Logistic transform from x to p and logit transform from p to xlogistic logistic.grm logit
Combine two square matrices to have a lower off diagonal for one, upper off diagonal for the otherlowerUpper
Create a keys matrix for use by score.items or cluster.corkeys2list make.keys makePositiveKeys selectFromKeys
"Manhattan" plots of correlations with a set of criteria.manhattan
Calculate univariate or multivariate (Mardia's test) skew and kurtosis for a vector, matrix, or data.framekurtosi mardia skew
Sort the elements of a correlation matrix to reflect factor loadingsmat.sort matSort
A function to add two vectors or matrices%+% matrix.addition
Estimate and display direct and indirect effects of mediators and moderator in path modelsmediate mediate.diagram moderate.diagram
Find correlations for mixtures of continuous, polytomous, and dichotomous variablesmixed.cor mixedCor
Find von Neuman's Mean Square of Successive DifferencesautoR mssd rmssd
Multiple histograms with density and normal fits on one pagehistBy histo.density multi.hist
Find and plot various reliability/gneralizability coefficients for multilevel datamlArrange mlPlot mlr multilevel.reliability
Calculate McDonald's omega estimates of general and total factor saturationdirectSl omega omegaDirect omegaFromSem omegah omegaSem
Graph hierarchical factor structuresomega.diagram omega.graph
Find and graph Mahalanobis squared distances to detect outliersoutlier
Find the probability of replication for an F, t, or r and estimate effect sizep.rep p.rep.f p.rep.r p.rep.t
Test the difference between (un)paired correlationspaired.r
SPLOM, histograms and correlations for a data matrixpairs.panels panel.cor panel.cor.scale panel.ellipse panel.hist panel.hist.density panel.lm panel.lm.ellipse panel.smoother
Count number of pairwise cases for a data set with missing (NA) data and impute values.count.pairwise pairwiseCount pairwiseCountBig pairwiseDescribe pairwiseImpute pairwisePlot pairwiseReport pairwiseSample pairwiseZero
Find miniscales (parcels) of size 2 or 3 from a set of itemskeysort parcels
Find the partial correlations for a set (x) of variables with set (y) removed.partial.r
Find the phi coefficient of correlation between two dichotomous variablesphi
A simple demonstration of the Pearson, phi, and polychoric corelationphi.demo
Convert a phi coefficient to a tetrachoric correlationphi2poly phi2tetra
Compute the Moore-Penrose Pseudo Inverse of a matrixPinv
Plotting functions for the psych package of class ``psych"plot.irt plot.poly plot.psych plot.residuals
Convert Cartesian factor loadings into polar coordinatespolar
Phi or Yule coefficient matrix to polychoric coefficient matrixphi2poly.matrix polychor.matrix Yule2phi.matrix Yule2poly.matrix
Prediction function for factor analysis, principal components (pca), bestScalespredict.psych
Find the predicted validities of a set of scales based on item statisticsitem.validity predicted.validity validityItem
Principal components analysis (PCA)pca principal
Print and summary functions for the psych classprint.psych summary.psych
Perform Procustes,bifactor, promax or targeted rotations and return the inter factor angles.bifactor biquartimin equamax faRotate Procrustes Promax target.rot TargetQ TargetT varimin vgQ.bimin vgQ.targetQ vgQ.varimin
Miscellaneous helper functions for the psych packageacs char2numeric cor2 cs fromTo isCorrelation isCovariance levels2numeric lowerCor lowerMat matMult misc nchar2numeric progressBar psych.misc reflect SAPAfy shannon tableF test.all
Tests of significance for correlationsr.test
Correct correlations for restriction of range. (Thorndike Case 2)rangeCorrection
Reports 7 different estimates of scale reliabity including alpha, omega, split halfplot.reliability reliability
Function to convert scores to ``conventional " metricsrescale
Extract residuals from various psych objectsresid.psych residuals.psych
Reverse the coding of selected items prior to scale analysisreverse.code
Root Mean Squared Error of Approximation from chisq, df, and nRMSEA
Three measures of the correlations between sets of variablesRV
3 Measures of ability: SATV, SATQ, ACTsat.act
Test the adequacy of simple choice, logistic, or Thurstonian scaling.scaling.fits
Draw a scatter plot with associated X and Y histograms, densities and correlationscatter.hist scatterHist
Apply the Schmid Leiman transformation to a correlation matrixschmid
12 variables created by Schmid and Leiman to show the Schmid-Leiman TransformationChen Schmid schmid.leiman West
Score scales and find Cronbach's alpha as well as associated statisticsscore.alpha
Score multiple choice items and provide basic test statisticsscore.multiple.choice
Find Item Response Theory (IRT) based scores for dichotomous or polytomous itemsirt.se irt.stats.like irt.tau make.irt.stats score.irt score.irt.2 score.irt.poly scoreIrt scoreIrt.1pl scoreIrt.2pl
Score item composite scales and find Cronbach's alpha, Guttman lambda 6 and item whole correlationsremoveMissing response.frequencies responseFrequency score.items scoreFast scoreItems scoreVeryFast
Find correlations of composite variables (corrected for overlap) from a larger matrix.cluster.cor scoreBy scoreOverlap
Score items using regression or correlation based weightsscoreWtd
A utility for basic data cleaning and recoding. Changes values outside of minimum and maximum limits to NA.scrub
Find the Standard deviation for a vector, matrix, or data.frame - do not return error if there are no casesSD
Functions to simulate psychological/psychometric data.sim sim.minor sim.simplex
Simulate a 3 way balanced ANOVA or linear model, with or without repeated measures.sim.anova
Simulate a congeneric data set with or without minor factorscongeneric.sim make.congeneric sim.congeneric
Create a population or sample correlation matrix, perhaps with hierarchical structure.make.hierarchical sim.bonds sim.hierarchical
Functions to simulate psychological/psychometric data.sim.irt sim.npl sim.npn sim.poly sim.poly.ideal sim.poly.ideal.npl sim.poly.ideal.npn sim.poly.mat sim.poly.npl sim.poly.npn sim.rasch
Generate simulated data structures for circumplex, spherical, or simple structurecirc.sim con2cat item.dichot item.sim sim.circ sim.dichot sim.item sim.spherical
Simulate multilevel data with specified within group and between group correlationssim.multi sim.multilevel
Further functions to simulate psychological/psychometric data.sim.general sim.omega sim.parallel
Create correlation matrices or data matrices with a particular measurement and structural modelsim.correlation sim.structural sim.structure simCor
create VSS like datasim.VSS VSS.sim VSS.simulate
Simulations of circumplex and simple structurecirc.sim.plot circ.simulation simulation.circ
A small example data set taken from a larger data setsmall.msq
Find the Squared Multiple Correlation (SMC) of each variable with the remaining variables in a matrixsmc
Make "radar" or "spider" plots.radar spider
Alternative estimates of test reliabiityglb glb.fa guttman splitHalf tenberge
Find statistics (including correlations) within and between groups for basic multilevel analysesfaBy statsBy statsBy.boot statsBy.boot.summary
Draw a structural equation model specified by two measurement models and a structural modellavaan.diagram sem.diagram sem.graph structure.diagram structure.graph structure.sem
Create factor model matrices from an input listphi.list structure.list
Form a super matrix from two sub matrices.super.matrix superCor superMatrix
Convert a table with counts to a matrix or data.frame representing those counts.table2df table2matrix
Data set testing causal direction in presumed media influencepmi Tal.Or Tal_Or tctg
A simple demonstration (and test) of various IRT scoring algorthims.test.irt
Testing of functions in the psych packagetest.psych
Find various test-retest statistics, including test, person and item reliabilitytestReliability testRetest
Tetrachoric, polychoric, biserial and polyserial correlations from various types of inputbiserial poly.mat polychoric polydi polyserial tetrachor tetrachoric
Thurstone Case V scalingthurstone
Find the trace of a square matrixtr
9 Cognitive variables discussed by Tucker and Lewis (1973)Tucker
Several indices of the unidimensionality of a set of variables.unidim
Apply the Very Simple Structure, MAP, and other criteria to determine the appropriate number of factors.eigenCi MAP nfactors VSS vss vssSelect
Compare real and random VSS solutionsVSS.parallel
Plot VSS fitsVSS.plot
Plot the successive eigen values for a scree testscree VSS.scree
Find the Winsorized scores, means, sds or variances for a vector, matrix, or data.framewinsor winsor.mean winsor.means winsor.sd winsor.var
An example of the distinction between within group and between group correlationswithinBetween
From a two by two table, find the Yule coefficients of association, convert to phi, or tetrachoric, recreate table the table to create the Yule coefficient.Yule Yule.inv Yule2phi Yule2poly Yule2tetra YuleBonett YuleCor