| Title: | Real Datasets for Assessing Ecological Inference Algorithms |
|---|---|
| Description: | Provides more than 550 data sets of actual election results. Each of the data sets includes aggregate party and candidate outcomes at the voting unit (polling stations) level and two-way cross-tabulated results at the district level. These data sets can be used to assess ecological inference algorithms devised for estimating RxC (global) ecological contingency tables using exclusively aggregate results from voting units. Reference: Pavía (2022) <doi:10.1177/08944393211040808>. |
| Authors: | Jose M. Pavía [aut, cre]
|
| Maintainer: | Jose M. Pavía <[email protected]> |
| License: | EPL | CC BY 4.0 | file LICENSE |
| Version: | 0.0.1-3 |
| Built: | 2024-12-13 06:31:59 UTC |
| Source: | CRAN |
This tibble contains 69 data sets corresponding to the 2002 New Zealand General Election. Each data set includes party and candidate vote results by voting unit as well as their associate cross-distributions (for votes and percentages) at the district (electorate) level.
data(ei_NZ_2002)data(ei_NZ_2002)
A tibble containing 69 observations and 6 variables:
Number_of_districtNumber assigned to the district/electorate by the New Zealand Electoral Commission.
DistrictName of the district/electorate.
Votes_to_partiesA tibble for each electorate/district with the party votes recorded in each voting unit of the district.
Votes_to_candidatesA tibble for each electorate/district with the candidate votes recorded in each voting unit of the district.
District_cross_votesA tibble for each electorate/district with the parties-candidates cross-distribution of votes in the entire electorate/district.
District_cross_percentagesA tibble for each electorate/district, with the parties to candidates voter transition probabilities (in percentages) in the entire electorate/district.
Description of the Votes_to_parties, Votes_to_candidates, District_cross_votes and District_cross_percentages variables in more detail, where N(i), R(i) and C(i) denote, respectively, the number of voting units, party voting options and candidate voting options in district i:
Votes_to_parties: A list of 69 tibbles/data.frames, with each data.frame containing N(i) observations and 2+R(i) variables. The two first variables, City and Address inform, respectively, about the place in the district where the voting unit is located and the voting unit address. The rest of the columns correspond to the votes gained by the different party voting options competing in the district. The orders of the voting units in Votes_to_parties and Votes_to_candidates coincide.
Votes_to_candidates: A list of 69 tibbles/data.frames, with each data.frame containing N(i) observations and 2+C(i) variables. The two first variables, City and Address inform, respectively, about the place in the district where the voting unit is located and the voting unit address. The rest of the columns correspond to the votes gained by the different candidate voting options competing in the district. The orders of the voting units in Votes_to_candidates and Votes_to_parties coincide.
District_cross_votes: A list of 69 tibbles/data.frames, with each data.frame containing R(i) rows and 1+C(i) columns (variables). The first variable, which is labelled after the name of the district, contains the names of the parties in the same order than in corresponding Votes_to_parties tibble, the rest of the variables (columns), ordered as in the corresponding Votes_to_candidates tibble, are labelled as the candidate voting options.
District_cross_percentages: A list of 69 tibbles/data.frames, with each data.frame containing R(i) rows and 1+C(i) columns (variables). The first variable, which is labelled after the name of the district, contains the names of the parties in the same order than in corresponding Votes_to_parties tibble, the rest of the variables (columns), ordered as in the corresponding Votes_to_candidates tibble, are labelled as the candidate voting options.
The New Zealand Electoral Commission had no involvement in preparing these data sets. The raw data has been pre-processed in order to guarantee their straighforward usefulness in ecological inference procedures. Some small discrepancies exist among the figures in District_cross_percentages and District_cross_votes. The percentages are a direct translation of the published data, whereas the vote counts have been adjusted using integer linear programming to make them congruents with the figures in Votes_to_parties and Votes_to_candidates. More details in Pavia (2021). For the official results, visit https://www.electionresults.govt.nz.
Jose M. Pavia, [email protected]
Own elaboration from data available in https://www.electionresults.govt.nz, retrieved 19 January 2019.
Pavia, JM (2021). ei.Datasets: Real datasets for assessing ecological inference algorithms, Social Science Computer Review, forthcoming.
ei_NZ_2005 ei_NZ_2008 ei_NZ_2011
ei_NZ_2014 ei_NZ_2017 ei_NZ_2020
ei_SCO_2007
This tibble contains 69 data sets corresponding to the 2005 New Zealand General Election. Each data set includes party and candidate vote results by voting unit as well as their associate cross-distributions (for votes and percentages) at the district (electorate) level.
data(ei_NZ_2005)data(ei_NZ_2005)
A tibble containing 69 observations and 6 variables:
Number_of_districtNumber assigned to the district/electorate by the New Zealand Electoral Commission.
DistrictName of the district/electorate.
Votes_to_partiesA tibble for each electorate/district with the party votes recorded in each voting unit of the district.
Votes_to_candidatesA tibble for each electorate/district with the candidate votes recorded in each voting unit of the district.
District_cross_votesA tibble for each electorate/district with the parties-candidates cross-distribution of votes in the entire electorate/district.
District_cross_percentagesA tibble for each electorate/district, with the parties to candidates voter transition probabilities (in percentages) in the entire electorate/district.
Description of the Votes_to_parties, Votes_to_candidates, District_cross_votes and District_cross_percentages variables in more detail, where N(i), R(i) and C(i) denote, respectively, the number of voting units, party voting options and candidate voting options in district i:
Votes_to_parties: A list of 69 tibbles/data.frames, with each data.frame containing N(i) observations and 2+R(i) variables. The two first variables, City and Address inform, respectively, about the place in the district where the voting unit is located and the voting unit address. The rest of the columns correspond to the votes gained by the different party voting options competing in the district. The orders of the voting units in Votes_to_parties and Votes_to_candidates coincide.
Votes_to_candidates: A list of 69 tibbles/data.frames, with each data.frame containing N(i) observations and 2+C(i) variables. The two first variables, City and Address inform, respectively, about the place in the district where the voting unit is located and the voting unit address. The rest of the columns correspond to the votes gained by the different candidate voting options competing in the district. The orders of the voting units in Votes_to_candidates and Votes_to_parties coincide.
District_cross_votes: A list of 69 tibbles/data.frames, with each data.frame containing R(i) rows and 1+C(i) columns (variables). The first variable, which is labelled after the name of the district, contains the names of the parties in the same order than in corresponding Votes_to_parties tibble, the rest of the variables (columns), ordered as in the corresponding Votes_to_candidates tibble, are labelled as the candidate voting options.
District_cross_percentages: A list of 69 tibbles/data.frames, with each data.frame containing R(i) rows and 1+C(i) columns (variables). The first variable, which is labelled after the name of the district, contains the names of the parties in the same order than in corresponding Votes_to_parties tibble, the rest of the variables (columns), ordered as in the corresponding Votes_to_candidates tibble, are labelled as the candidate voting options.
The New Zealand Electoral Commission had no involvement in preparing these data sets. The raw data has been pre-processed in order to guarantee their straighforward usefulness in ecological inference procedures. Some small discrepancies exist among the figures in District_cross_percentages and District_cross_votes. The percentages are a direct translation of the published data, whereas the vote counts have been adjusted using integer linear programming to make them congruents with the figures in Votes_to_parties and Votes_to_candidates. More details in Pavia (2021). For the official results, visit https://www.electionresults.govt.nz.
Jose M. Pavia, [email protected]
Own elaboration from data available in https://www.electionresults.govt.nz, retrieved 19 January 2019.
ei.Datasets: Real datasets for assessing ecological inference algorithms, Social Science Computer Review, forthcoming.
ei_NZ_2002 ei_NZ_2008 ei_NZ_2011
ei_NZ_2014 ei_NZ_2017 ei_NZ_2020
ei_SCO_2007
This tibble contains 70 data sets corresponding to the 2008 New Zealand General Election. Each data set includes party and candidate vote results by voting unit as well as their associate cross-distributions (for votes and percentages) at the district (electorate) level.
data(ei_NZ_2008)data(ei_NZ_2008)
A tibble containing 70 observations and 6 variables:
Number_of_districtNumber assigned to the district/electorate by the New Zealand Electoral Commission.
DistrictName of the district/electorate.
Votes_to_partiesA tibble for each electorate/district with the party votes recorded in each voting unit of the district.
Votes_to_candidatesA tibble for each electorate/district with the candidate votes recorded in each voting unit of the district.
District_cross_votesA tibble for each electorate/district with the parties-candidates cross-distribution of votes in the entire electorate/district.
District_cross_percentagesA tibble for each electorate/district, with the parties to candidates voter transition probabilities (in percentages) in the entire electorate/district.
Description of the Votes_to_parties, Votes_to_candidates, District_cross_votes and District_cross_percentages variables in more detail, where N(i), R(i) and C(i) denote, respectively, the number of voting units, party voting options and candidate voting options in district i:
Votes_to_parties: A list of 70 tibbles/data.frames, with each data.frame containing N(i) observations and 2+R(i) variables. The two first variables, City and Address inform, respectively, about the place in the district where the voting unit is located and the voting unit address. The rest of the columns correspond to the votes gained by the different party voting options competing in the district. The orders of the voting units in Votes_to_parties and Votes_to_candidates coincide.
Votes_to_candidates: A list of 70 tibbles/data.frames, with each data.frame containing N(i) observations and 2+C(i) variables. The two first variables, City and Address inform, respectively, about the place in the district where the voting unit is located and the voting unit address. The rest of the columns correspond to the votes gained by the different candidate voting options competing in the district. The orders of the voting units in Votes_to_candidates and Votes_to_parties coincide.
District_cross_votes: A list of 70 tibbles/data.frames, with each data.frame containing R(i) rows and 1+C(i) columns (variables). The first variable, which is labelled after the name of the district, contains the names of the parties in the same order than in corresponding Votes_to_parties tibble, the rest of the variables (columns), ordered as in the corresponding Votes_to_candidates tibble, are labelled as the candidate voting options.
District_cross_percentages: A list of 70 tibbles/data.frames, with each data.frame containing R(i) rows and 1+C(i) columns (variables). The first variable, which is labelled after the name of the district, contains the names of the parties in the same order than in corresponding Votes_to_parties tibble, the rest of the variables (columns), ordered as in the corresponding Votes_to_candidates tibble, are labelled as the candidate voting options.
The New Zealand Electoral Commission had no involvement in preparing these data sets. The raw data has been pre-processed in order to guarantee their straighforward usefulness in ecological inference procedures. Some small discrepancies exist among the figures in District_cross_percentages and District_cross_votes. The percentages are a direct translation of the published data, whereas the vote counts have been adjusted using integer linear programming to make them congruents with the figures in Votes_to_parties and Votes_to_candidates. More details in Pavia (2021). For the official results, visit https://www.electionresults.govt.nz.
Jose M. Pavia, [email protected]
Own elaboration from data available in https://www.electionresults.govt.nz, retrieved 19 January 2019.
ei.Datasets: Real datasets for assessing ecological inference algorithms, Social Science Computer Review, forthcoming.
ei_NZ_2002 ei_NZ_2005 ei_NZ_2011
ei_NZ_2014 ei_NZ_2017 ei_NZ_2020
ei_SCO_2007
This tibble contains 70 data sets corresponding to the 2011 New Zealand General Election. Each data set includes party and candidate vote results by voting unit as well as their associate cross-distributions (for votes and percentages) at the district (electorate) level.
data(ei_NZ_2011)data(ei_NZ_2011)
A tibble containing 70 observations and 6 variables:
Number_of_districtNumber assigned to the district/electorate by the New Zealand Electoral Commission.
DistrictName of the district/electorate.
Votes_to_partiesA tibble for each electorate/district with the party votes recorded in each voting unit of the district.
Votes_to_candidatesA tibble for each electorate/district with the candidate votes recorded in each voting unit of the district.
District_cross_votesA tibble for each electorate/district with the parties-candidates cross-distribution of votes in the entire electorate/district.
District_cross_percentagesA tibble for each electorate/district, with the parties to candidates voter transition probabilities (in percentages) in the entire electorate/district.
Description of the Votes_to_parties, Votes_to_candidates, District_cross_votes and District_cross_percentages variables in more detail, where N(i), R(i) and C(i) denote, respectively, the number of voting units, party voting options and candidate voting options in district i:
Votes_to_parties: A list of 70 tibbles/data.frames, with each data.frame containing N(i) observations and 2+R(i) variables. The two first variables, City and Address inform, respectively, about the place in the district where the voting unit is located and the voting unit address. The rest of the columns correspond to the votes gained by the different party voting options competing in the district. The orders of the voting units in Votes_to_parties and Votes_to_candidates coincide.
Votes_to_candidates: A list of 70 tibbles/data.frames, with each data.frame containing N(i) observations and 2+C(i) variables. The two first variables, City and Address inform, respectively, about the place in the district where the voting unit is located and the voting unit address. The rest of the columns correspond to the votes gained by the different candidate voting options competing in the district. The orders of the voting units in Votes_to_candidates and Votes_to_parties coincide.
District_cross_votes: A list of 70 tibbles/data.frames, with each data.frame containing R(i) rows and 1+C(i) columns (variables). The first variable, which is labelled after the name of the district, contains the names of the parties in the same order than in corresponding Votes_to_parties tibble, the rest of the variables (columns), ordered as in the corresponding Votes_to_candidates tibble, are labelled as the candidate voting options.
District_cross_percentages: A list of 70 tibbles/data.frames, with each data.frame containing R(i) rows and 1+C(i) columns (variables). The first variable, which is labelled after the name of the district, contains the names of the parties in the same order than in corresponding Votes_to_parties tibble, the rest of the variables (columns), ordered as in the corresponding Votes_to_candidates tibble, are labelled as the candidate voting options.
The New Zealand Electoral Commission had no involvement in preparing these data sets. The raw data has been pre-processed in order to guarantee their straighforward usefulness in ecological inference procedures. Some small discrepancies exist among the figures in District_cross_percentages and District_cross_votes. The percentages are a direct translation of the published data, whereas the vote counts have been adjusted using integer linear programming to make them congruents with the figures in Votes_to_parties and Votes_to_candidates. More details in Pavia (2021). For the official results, visit https://www.electionresults.govt.nz.
Jose M. Pavia, [email protected]
Own elaboration from data available in https://www.electionresults.govt.nz, retrieved 19 January 2019.
ei.Datasets: Real datasets for assessing ecological inference algorithms, Social Science Computer Review, forthcoming.
ei_NZ_2002 ei_NZ_2005 ei_NZ_2008
ei_NZ_2014 ei_NZ_2017 ei_NZ_2020
ei_SCO_2007
This tibble contains 71 data sets corresponding to the 2014 New Zealand General Election. Each data set includes party and candidate vote results by voting unit as well as their associate cross-distributions (for votes and percentages) at the district (electorate) level.
data(ei_NZ_2014)data(ei_NZ_2014)
A tibble containing 71 observations and 6 variables:
Number_of_districtNumber assigned to the district/electorate by the New Zealand Electoral Commission.
DistrictName of the district/electorate.
Votes_to_partiesA tibble for each electorate/district with the party votes recorded in each voting unit of the district.
Votes_to_candidatesA tibble for each electorate/district with the candidate votes recorded in each voting unit of the district.
District_cross_votesA tibble for each electorate/district with the parties-candidates cross-distribution of votes in the entire electorate/district.
District_cross_percentagesA tibble for each electorate/district, with the parties to candidates voter transition probabilities (in percentages) in the entire electorate/district.
Description of the Votes_to_parties, Votes_to_candidates, District_cross_votes and District_cross_percentages variables in more detail, where N(i), R(i) and C(i) denote, respectively, the number of voting units, party voting options and candidate voting options in district i:
Votes_to_parties: A list of 71 tibbles/data.frames, with each data.frame containing N(i) observations and 2+R(i) variables. The two first variables, City and Address inform, respectively, about the place in the district where the voting unit is located and the voting unit address. The rest of the columns correspond to the votes gained by the different party voting options competing in the district. The orders of the voting units in Votes_to_parties and Votes_to_candidates coincide.
Votes_to_candidates: A list of 71 tibbles/data.frames, with each data.frame containing N(i) observations and 2+C(i) variables. The two first variables, City and Address inform, respectively, about the place in the district where the voting unit is located and the voting unit address. The rest of the columns correspond to the votes gained by the different candidate voting options competing in the district. The orders of the voting units in Votes_to_candidates and Votes_to_parties coincide.
District_cross_votes: A list of 71 tibbles/data.frames, with each data.frame containing R(i) rows and 1+C(i) columns (variables). The first variable, which is labelled after the name of the district, contains the names of the parties in the same order than in corresponding Votes_to_parties tibble, the rest of the variables (columns), ordered as in the corresponding Votes_to_candidates tibble, are labelled as the candidate voting options.
District_cross_percentages: A list of 71 tibbles/data.frames, with each data.frame containing R(i) rows and 1+C(i) columns (variables). The first variable, which is labelled after the name of the district, contains the names of the parties in the same order than in corresponding Votes_to_parties tibble, the rest of the variables (columns), ordered as in the corresponding Votes_to_candidates tibble, are labelled as the candidate voting options.
The New Zealand Electoral Commission had no involvement in preparing these data sets. The raw data has been pre-processed in order to guarantee their straighforward usefulness in ecological inference procedures. Some small discrepancies exist among the figures in District_cross_percentages and District_cross_votes. The percentages are a direct translation of the published data, whereas the vote counts have been adjusted using integer linear programming to make them congruents with the figures in Votes_to_parties and Votes_to_candidates. More details in Pavia (2021). For the official results, visit https://www.electionresults.govt.nz.
Jose M. Pavia, [email protected]
Own elaboration from data available in https://www.electionresults.govt.nz, retrieved 19 January 2019.
ei.Datasets: Real datasets for assessing ecological inference algorithms, Social Science Computer Review, forthcoming.
ei_NZ_2002 ei_NZ_2005 ei_NZ_2008
ei_NZ_2011 ei_NZ_2017 ei_NZ_2020
ei_SCO_2007
This tibble contains 71 data sets corresponding to the 2017 New Zealand General Election. Each data set includes party and candidate vote results by voting unit as well as their associate cross-distributions (for votes and percentages) at the district (electorate) level.
data(ei_NZ_2017)data(ei_NZ_2017)
A tibble containing 71 observations and 6 variables:
Number_of_districtNumber assigned to the district/electorate by the New Zealand Electoral Commission.
DistrictName of the district/electorate.
Votes_to_partiesA tibble for each electorate/district with the party votes recorded in each voting unit of the district.
Votes_to_candidatesA tibble for each electorate/district with the candidate votes recorded in each voting unit of the district.
District_cross_votesA tibble for each electorate/district with the parties-candidates cross-distribution of votes in the entire electorate/district.
District_cross_percentagesA tibble for each electorate/district, with the parties to candidates voter transition probabilities (in percentages) in the entire electorate/district.
Description of the Votes_to_parties, Votes_to_candidates, District_cross_votes and District_cross_percentages variables in more detail, where N(i), R(i) and C(i) denote, respectively, the number of voting units, party voting options and candidate voting options in district i:
Votes_to_parties: A list of 71 tibbles/data.frames, with each data.frame containing N(i) observations and 2+R(i) variables. The two first variables, City and Address inform, respectively, about the place in the district where the voting unit is located and the voting unit address. The rest of the columns correspond to the votes gained by the different party voting options competing in the district. The orders of the voting units in Votes_to_parties and Votes_to_candidates coincide.
Votes_to_candidates: A list of 71 tibbles/data.frames, with each data.frame containing N(i) observations and 2+C(i) variables. The two first variables, City and Address inform, respectively, about the place in the district where the voting unit is located and the voting unit address. The rest of the columns correspond to the votes gained by the different candidate voting options competing in the district. The orders of the voting units in Votes_to_candidates and Votes_to_parties coincide.
District_cross_votes: A list of 71 tibbles/data.frames, with each data.frame containing R(i) rows and 1+C(i) columns (variables). The first variable, which is labelled after the name of the district, contains the names of the parties in the same order than in corresponding Votes_to_parties tibble, the rest of the variables (columns), ordered as in the corresponding Votes_to_candidates tibble, are labelled as the candidate voting options.
District_cross_percentages: A list of 71 tibbles/data.frames, with each data.frame containing R(i) rows and 1+C(i) columns (variables). The first variable, which is labelled after the name of the district, contains the names of the parties in the same order than in corresponding Votes_to_parties tibble, the rest of the variables (columns), ordered as in the corresponding Votes_to_candidates tibble, are labelled as the candidate voting options.
The New Zealand Electoral Commission had no involvement in preparing these data sets. The raw data has been pre-processed in order to guarantee their straighforward usefulness in ecological inference procedures. Some small discrepancies exist among the figures in District_cross_percentages and District_cross_votes. The percentages are a direct translation of the published data, whereas the vote counts have been adjusted using integer linear programming to make them congruents with the figures in Votes_to_parties and Votes_to_candidates. More details in Pavia (2021). For the official results, visit https://www.electionresults.govt.nz.
Jose M. Pavia, [email protected]
Own elaboration from data available in https://www.electionresults.govt.nz, retrieved 19 January 2019.
ei.Datasets: Real datasets for assessing ecological inference algorithms, Social Science Computer Review, forthcoming.
ei_NZ_2002 ei_NZ_2005 ei_NZ_2008
ei_NZ_2011 ei_NZ_2014 ei_NZ_2020
ei_SCO_2007
This tibble contains 72 data sets corresponding to the 2020 New Zealand General Election. Each data set includes party and candidate vote results by voting unit as well as their associate cross-distributions (for votes and percentages) at the district (electorate) level.
data(ei_NZ_2020)data(ei_NZ_2020)
A tibble containing 72 observations and 6 variables:
Number_of_districtNumber assigned to the district/electorate by the New Zealand Electoral Commission.
DistrictName of the district/electorate.
Votes_to_partiesA tibble for each electorate/district with the party votes recorded in each voting unit of the district.
Votes_to_candidatesA tibble for each electorate/district with the candidate votes recorded in each voting unit of the district.
District_cross_votesA tibble for each electorate/district with the parties-candidates cross-distribution of votes in the entire electorate/district.
District_cross_percentagesA tibble for each electorate/district, with the parties to candidates voter transition probabilities (in percentages) in the entire electorate/district.
Description of the Votes_to_parties, Votes_to_candidates, District_cross_votes and District_cross_percentages variables in more detail, where N(i), R(i) and C(i) denote, respectively, the number of voting units, party voting options and candidate voting options in district i:
Votes_to_parties: A list of 72 tibbles/data.frames, with each data.frame containing N(i) observations and 2+R(i) variables. The two first variables, City and Address inform, respectively, about the place in the district where the voting unit is located and the voting unit address. The rest of the columns correspond to the votes gained by the different party voting options competing in the district. The orders of the voting units in Votes_to_parties and Votes_to_candidates coincide.
Votes_to_candidates: A list of 72 tibbles/data.frames, with each data.frame containing N(i) observations and 2+C(i) variables. The two first variables, City and Address inform, respectively, about the place in the district where the voting unit is located and the voting unit address. The rest of the columns correspond to the votes gained by the different candidate voting options competing in the district. The orders of the voting units in Votes_to_candidates and Votes_to_parties coincide.
District_cross_votes: A list of 72 tibbles/data.frames, with each data.frame containing R(i) rows and 1+C(i) columns (variables). The first variable, which is labelled after the name of the district, contains the names of the parties in the same order than in corresponding Votes_to_parties tibble, the rest of the variables (columns), ordered as in the corresponding Votes_to_candidates tibble, are labelled as the candidate voting options.
District_cross_percentages: A list of 72 tibbles/data.frames, with each data.frame containing R(i) rows and 1+C(i) columns (variables). The first variable, which is labelled after the name of the district, contains the names of the parties in the same order than in corresponding Votes_to_parties tibble, the rest of the variables (columns), ordered as in the corresponding Votes_to_candidates tibble, are labelled as the candidate voting options.
The New Zealand Electoral Commission had no involvement in preparing these data sets. The raw data has been pre-processed in order to guarantee their straighforward usefulness in ecological inference procedures. Some small discrepancies exist among the figures in District_cross_percentages and District_cross_votes. The percentages are a direct translation of the published data, whereas the vote counts have been adjusted using integer linear programming to make them congruents with the figures in Votes_to_parties and Votes_to_candidates. More details in Pavia (2021). For the official results, visit https://www.electionresults.govt.nz.
Jose M. Pavia, [email protected]
Own elaboration from data available in https://www.electionresults.govt.nz, retrieved 23 January 2021.
ei.Datasets: Real datasets for assessing ecological inference algorithms, Social Science Computer Review, forthcoming.
ei_NZ_2002 ei_NZ_2005 ei_NZ_2008
ei_NZ_2011 ei_NZ_2014 ei_NZ_2017
ei_SCO_2007
This tibble contains 73 data sets corresponding to the 2007 Scottish National Assembly election. Each data set includes party and candidate vote results by voting unit as well as their associate cross-distributions (for votes and percentages) at the district (constituency) level.
data(ei_SCO_2007)data(ei_SCO_2007)
A tibble containing 73 observations and 6 variables:
Number_of_districtNumber assigned to the district/constituency by the New Zealand Electoral Commission.
DistrictName of the district/constituency.
Votes_to_partiesA tibble for each constituency/district with the party votes recorded in each voting unit of the district.
Votes_to_candidatesA tibble for each constituency/district with the candidate votes recorded in each voting unit of the district.
District_cross_votesA tibble for each constituency/district with the parties-candidates cross-distribution of votes in the entire constituency/district.
District_cross_percentagesA tibble for each constituency/district, with the parties to candidates voter transition probabilities (in percentages) in the entire constituency/district.
Description of the Votes_to_parties, Votes_to_candidates, District_cross_votes and District_cross_percentages variables in more detail, where N(i), R(i) and C(i) denote, respectively, the number of voting units, party voting options and candidate voting options in district i:
Votes_to_parties: A list of 73 tibbles/data.frames, with each data.frame containing N(i) observations and 2+R(i) variables. The two first variables, Polling and Address inform, respectively, about the code in the district assigned to the voting unit and the voting unit address. The rest of the columns correspond to the votes gained by the different party voting options competing in the district. The orders of the voting units in Votes_to_parties and Votes_to_candidates coincide.
Votes_to_candidates: A list of 73 tibbles/data.frames, with each data.frame containing N(i) observations and 2+C(i) variables. The two first variables, Polling and Address inform, respectively, about the code in the district assigned to the voting unit and the voting unit address. The rest of the columns correspond to the votes gained by the different candidate voting options competing in the district. The orders of the voting units in Votes_to_candidates and Votes_to_parties coincide.
District_cross_votes: A list of 73 tibbles/data.frames, with each data.frame containing R(i) rows and 1+C(i) columns (variables). The first variable, which is labelled after the name of the district, contains the names of the parties in the same order than in corresponding Votes_to_parties tibble, the rest of the variables (columns), ordered as in the corresponding Votes_to_candidates tibble, are labelled as the candidate voting options.
District_cross_percentages: A list of 73 tibbles/data.frames, with each data.frame containing R(i) rows and 1+C(i) columns (variables). The first variable, which is labelled after the name of the district, contains the names of the parties in the same order than in corresponding Votes_to_parties tibble, the rest of the variables (columns), ordered as in the corresponding Votes_to_candidates tibble, are labelled as the candidate voting options.
Jose M. Pavia, [email protected]
Own elaboration from raw data downloading from the Scotland Electoral Office website in 2011 by Carolina Plescia. These data are not longer available in that site.
ei.Datasets: Real datasets for assessing ecological inference algorithms, Social Science Computer Review, forthcoming.
ei_NZ_2002 ei_NZ_2005 ei_NZ_2008
ei_NZ_2011 ei_NZ_2014 ei_NZ_2017
ei_NZ_2020
Merge small parties and also small candidates by, respectively, aggregating them in the options 'Other parties votes' and 'Other candidates votes'.
merge_small_options(x, min.party, min.candidate)merge_small_options(x, min.party, min.candidate)
x |
A tibble with the same components and structure as the tibbles in the |
min.party |
A number between 0 and 100. Those parties which individually did not reach at least min.party% of the election-district vote are grouped in the option ‘Other parties votes’. |
min.candidate |
A number between 0 and 100. Those candidates which individually did not reach at least min.candididate% of the election-district vote are grouped in the option ‘Other candidates votes’. |
A tibble similar to x with small parties and candidates merged on, respectively, ‘Other parties votes’
and ‘Other candidates votes’, with min.party and min.candidate used to determine when an electoral
option is small.
Jose M. Pavia, [email protected]
Pavia, JM (2021). ei.Datasets: Real datasets for assessing ecological inference algorithms, Social Science Computer Review, forthcoming.
ei_NZ_2002 ei_NZ_2005 ei_NZ_2008
ei_NZ_2011 ei_NZ_2014 ei_NZ_2017
ei_NZ_2020 ei_SCO_2007
collapsed.tibble <- merge_small_options(x = ei_NZ_2020, min.party = 3, min.candidate = 5)collapsed.tibble <- merge_small_options(x = ei_NZ_2020, min.party = 3, min.candidate = 5)