https://github.com/bonstats/undecided-voters-us-pres-elections
Data and code for "Polling bias and undecided voter allocations: US Presidential elections, 2004 - 2016"
https://github.com/bonstats/undecided-voters-us-pres-elections
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Keywords
bayesian-inference
election-data
election-polling
elections
presidential-election
r
stan
total-survey-error
Last synced: 5 months ago
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Data and code for "Polling bias and undecided voter allocations: US Presidential elections, 2004 - 2016"
Basic Info
- Host: GitHub
- Owner: bonStats
- License: mit
- Language: R
- Default Branch: master
- Size: 2.56 MB
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Topics
bayesian-inference
election-data
election-polling
elections
presidential-election
r
stan
total-survey-error
Created over 7 years ago
· Last pushed over 4 years ago
https://github.com/bonStats/undecided-voters-us-pres-elections/blob/master/
# Data and code to accompany paper "Polling bias and undecided voter allocations: US Presidential elections, 2004 - 2016" Cite as: Bon, J. J., Ballard, T. and Baffour, B. (2019), Polling bias and undecided voter allocations: US presidential elections, 20042016. Journal of the Royal Statistical Society, Series A (Statistics in Society), 182(2): 467-493. doi:[10.1111/rssa.12414](http://dx.doi.org/10.1111/rssa.12414). [Link to paper on journal website](http://dx.doi.org/10.1111/rssa.12414) [Link to paper on arXiv](https://arxiv.org/abs/1703.09430) - Corresponding Author: Joshua J Bon - Web: http://joshuabon.com - Github: https://github.com/bonStats/undecided-voters-us-pres-elections/ ## Directory description - Top: contains all `.R` code for running models and reproducing plots and tables in the paper - `data/`: Contain the state-level polling and voting data - `stan_models/`: contains `.stan` code that define (and estimate by HMC) the models - `fitted_models/`: Folder for fitted `.stan` models and summary outputs from those models - `eda/`: Contains example(s) of exploratory data analysis, including Figure 1 in the paper. The `fitted_models/` folder may be empty due to large size of files. Run the models and posterior calculations to populate. ## Data description Two data sets are in the `data/` directory. Please cite the above paper if using the dataset(s). ### Election results: `us-pres-state-voting-2004-2016.*` This data contains the election *results* for the 2004, 2008, 2012, and 2016 US presidential election by state. It is in both `.csv` and `.rds` (`tibble`) format. It has columns: - `state`: State names and Washington D.C. (e.g. `"washington-d-c"`) - `year`: Presidential election year: `2004`, `2008`, `2012`, `2016` - `state_year`: Concatenation of `state` and `year`: (e.g. `washington-d-c_2016`) - `state_year_id`: Unique integer ids for `state_year` - `Dem_vote`: Vote percentage won by Democratic candidate (`0`-`100`) - `Rep_vote`: Vote percentage won by Republican candidate (`0`-`100`) - `short_state`: Two character state id (e.g. `DC`) - `result_margin6`: Category for margin of voting *result*. Strong Dem. win (margin > 6%), Strong Rep. win (margin > 6%), or close margin (margin < 6%) - `year_id`: Unique integer ids for `year` ### Pre-election polls: `us-pres-state-polling-2004-2016.*` This data contains the election *polls* for the 2004, 2008, 2012, and 2016 US presidential election by state. It is in both `.csv` and `.rds` (`tibble`) format. It has columns: - `Dem_poll`: Polled percentage support for Democratic candidate (`0`-`100`) - `Rep_poll`: Polled percentage support for Republican candidate (`0`-`100`) - `Undecided`: Polled percentage of undecided voters (`0`-`100` and `NA`) - `sample_size`: Reported sample size of poll - `mean_days_to_election`: Number of days until election, measured as mean of start and end date of poll - `start_days_to_election`: Number of days until election, measured from start date of poll - `end_days_to_election`: Number of days until election, measured from end date of poll - `state`: State names and Washington D.C. (e.g. `"washington-d-c"`) - `year`: Presidential election year: `2004`, `2008`, `2012`, `2016` - `state_year`: Concatenation of `state` and `year`: (e.g. `washington-d-c_2016`) - `pollster`: Original name of polling agency or agencies - `state_year_id`: Unique integer ids for `state_year` - `pollster2`: Cleaned name of polling agency or agencies - `year_id`: Unique integer ids for `year` - `result_margin6`: Category for margin of voting *result*. Strong Dem. win (margin > 6%), Strong Rep. win (margin > 6%), or close margin (margin < 6%) - `rmargin_year`: `result_margin6` concatenated with `year` - `rmargin_year_id`: Unique integer ids for `rmargin_year` - `pollster_grp`: Further cleaned and grouped polling agencies or institutes - `pollster_id`: Unique integer ids for `pollster_grp` ## R code description - `state-polls-original-model.R`: Fit original SRGG model - `state-polls-extended-model-proportionate.R`: Fit extended SRGG model with baseline *proportionate* split of undecided voters - `state-polls-extended-model-even.R`: Fit extended SRGG model with baseline *even* split of undecided voters - `posterior-calcs.R`: Calculate additional posterior quantities from the model - `paper-outputs.R`: Reproduce all plots and tables for the paper ## Session Info ``` sessionInfo() #> R version 3.5.1 (2018-07-02) #> Platform: x86_64-apple-darwin15.6.0 (64-bit) #> Running under: macOS High Sierra 10.13.6 #> #> Matrix products: default #> BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib #> LAPACK: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRlapack.dylib #> #> locale: #> [1] en_AU.UTF-8/en_AU.UTF-8/en_AU.UTF-8/C/en_AU.UTF-8/en_AU.UTF-8 #> #> attached base packages: #> [1] parallel stats graphics grDevices utils datasets methods base #> #> other attached packages: #> [1] shinystan_2.5.0 shiny_1.1.0 gtools_3.8.1 plyr_1.8.4 #> [5] rstan_2.17.3 StanHeaders_2.17.2 rv_2.3.2 stringr_1.3.1 #> [9] scales_1.0.0 ggplot2_3.0.0 bindrcpp_0.2.2 dplyr_0.7.6 #> #> loaded via a namespace (and not attached): #> [1] Rcpp_0.12.18 lattice_0.20-35 zoo_1.8-4 assertthat_0.2.0 digest_0.6.16 #> [6] utf8_1.1.4 mime_0.5 R6_2.2.2 ggridges_0.5.0 stats4_3.5.1 #> [11] colourpicker_1.0 pillar_1.3.0 rlang_0.2.2 lazyeval_0.2.1 miniUI_0.1.1.1 #> [16] rstudioapi_0.7 DT_0.4 shinythemes_1.1.1 shinyjs_1.0 devtools_1.13.6 #> [21] readr_1.1.1 htmlwidgets_1.2 igraph_1.2.2 munsell_0.5.0 compiler_3.5.1 #> [26] httpuv_1.4.5 pkgconfig_2.0.2 base64enc_0.1-3 htmltools_0.3.6 tidyselect_0.2.4 #> [31] tibble_1.4.2 gridExtra_2.3 threejs_0.3.1 fansi_0.3.0 crayon_1.3.4 #> [36] withr_2.1.2 later_0.7.4 grid_3.5.1 xtable_1.8-3 gtable_0.2.0 #> [41] magrittr_1.5 cli_1.0.0 stringi_1.2.4 reshape2_1.4.3 promises_1.0.1 #> [46] dygraphs_1.1.1.6 xts_0.11-1 tools_3.5.1 glue_1.3.0 markdown_0.8 #> [51] purrr_0.2.5 hms_0.4.2 crosstalk_1.0.0 rsconnect_0.8.8 yaml_2.2.0 #> [56] inline_0.3.15 colorspace_1.3-2 bayesplot_1.6.0 memoise_1.1.0 bindr_0.1.1 ```
Owner
- Name: Joshua Bon
- Login: bonStats
- Kind: user
- Location: Meanjin / Brisbane
- Company: Queensland University of Technology
- Website: https://bonstats.github.io/
- Repositories: 3
- Profile: https://github.com/bonStats
Research statistician. Computation and a lot of dabbling. Centre for Data Science, Queensland University of Technology
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