| Version: | 0.5.3 |
| Title: | Dynamic Comparative Public Opinion |
| Description: | Estimates latent variables of public opinion cross-nationally and over time from sparse and incomparable survey data. 'DCPO' uses a population-level graded response model with country-specific item bias terms. Sampling is conducted with 'Stan'. References: Solt (2020) <doi:10.31235/osf.io/d5n9p>. |
| License: | GPL (≥ 3) |
| Encoding: | UTF-8 |
| LazyData: | true |
| ByteCompile: | true |
| Depends: | R (≥ 3.4.0), Rcpp (≥ 0.12.17), methods |
| Imports: | rstan (≥ 2.18.1), rstantools (≥ 2.0.0), beepr, dplyr, forcats, janitor, purrr, tibble, tidyr |
| LinkingTo: | StanHeaders (≥ 2.18.0), rstan (≥ 2.18.1), BH (≥ 1.66.0-1), Rcpp (≥ 0.12.0), RcppEigen (≥ 0.3.3.4.0) |
| Suggests: | knitr |
| SystemRequirements: | GNU make |
| NeedsCompilation: | yes |
| RoxygenNote: | 7.0.0 |
| Biarch: | true |
| Packaged: | 2020-05-28 13:23:22 UTC; fredsolt |
| Author: | Frederick Solt [aut, cre], Trustees of Columbia University [cph] |
| Maintainer: | Frederick Solt <frederick-solt@uiowa.edu> |
| Repository: | CRAN |
| Date/Publication: | 2020-05-29 12:50:02 UTC |
DCPO: Dynamic Comparative Public Opinion
Description
DCPO estimates dynamic comparative public opinion as a latent variable from survey data
References
Stan Development Team (2018). RStan: the R interface to Stan. R package version 2.18.2. http://mc-stan.org
Estimate Dynamic Comparative Public Opinion
Description
dcpo uses diverse survey data to estimate public opinion across countries and over time.
Usage
dcpo(dcpo_input, chime = TRUE, ...)
Arguments
dcpo_input |
a data frame of survey items and marginals generated by |
chime |
play chime when complete? |
... |
arguments to be passed to |
Details
dcpo, when passed a data frame dcpo_input of survey marginals created
by dcpo_setup, estimates a latent variable of public opinion. See rstan::stan for
additional options; stan defaults reset by dcpo are seed = 324, thin = 2,
cores = min(stan_args$chains, parallel::detectCores()/2), and control <- list(adapt_delta = 0.99, stepsize = 0.005, max_treedepth = 14)
Value
a stanfit object
Examples
out1 <- dcpo(demsup_data,
chains = 1,
iter = 300) # 1 chain/300 iterations for example purposes only; use defaults
Cross-validation testing for DCPO
Description
dcpo_xvt performs a single cross-validation test for DCPO
Usage
dcpo_xvt(
dcpo_input,
fold_number = 1,
number_of_folds = 10,
fold_seed = 324,
chime = TRUE,
...
)
Arguments
dcpo_input |
a data frame of survey items and marginals generated by |
fold_number |
an integer indicating the number of the fold to treated as test data in the current analysis |
number_of_folds |
an integer indicating the total number of folds |
fold_seed |
a seed for reproducibly randomly assigning observations to folds; when a complete set of k-fold cross-validations is to be performed, the same seed should be used for all |
chime |
play chime when complete? |
... |
arguments to be passed to |
Details
dcpo_xvt performs a single cross-validation test of a DCPO estimation. To perform
a complete k-fold cross-validation, call it repeatedly, changing only the fold_number argument.
Value
a stanfit object
Examples
# Single cross-validation test with 25% test set
demsup_xvtest_25pct <- dcpo_xvt(demsup_data,
number_of_folds = 4,
iter = 300,
chains = 1) # 1 chain/300 iterations for example only; use defaults
Support for Democracy in 51 Survey Datasets
Description
A dataset containing the prices and other attributes of almost 54,000 diamonds.
Usage
demsup_data
Format
A list of 15 elements
- K
an integer, the total number of countries in the data
- T
an integer, the total number of years in the data
- Q
an integer, the total number of distinct survey questions in the data
- R
an integer, the maximum number of response cutpoints in any survey question in the data
- N
an integer, the number of KTQR observations
- kk
a numeric vector of length N, the country of each observation
- tt
a numeric vector of length N, the year of each observation
a numeric vector of length N, the question of each observation
- rr
a numeric vector of length N, the response cutpoint of each observation
- y_r
a numeric vector of length N, the number of respondents who provided a response above the relevant cutpoint for each observation
- n_r
a numeric vector of length N, the total number of respondents for each observation
- fixed_cutp
a QxR matrix, a truth table indicating the question-cutpoint to be fixed at difficulty .5
- use_delta
a QxK tibble, a truth table indicating whether item difficulty should be estimated to vary by question-country to account for potential item-response bias
- data
an Nx14 tibble, the aggregate survey response dataset in its original format
- data_args
a list of length 3, indicating the arguments passed to DCPOtools::format_dcpo to generate demsup_data from demsup_data$data
Details
Data on aggregate support for democracy reported in 51 survey datasets in 998 country-years, formatted for use with the functions of the DCPO package
Source
demsup_data replicates the data employed in Claassen, Christopher. 2019. "Estimating Smooth Country-Year Panels of Public Opinion." Political Analysis 27(1):1-20. See https://github.com/fsolt/DCPOtools.
Get results of DCPO cross-validation testing
Description
get_xvt_results performs a single cross-validation test for dcpo's estimates of cross-national public opinion
Usage
get_xvt_results(dcpo_xvt_output, ci = 80)
Arguments
dcpo_xvt_output |
output from a single call to |
ci |
an integer indicating the desired width of credible interval for coverage testing; 80 is the default. |
Value
a stanfit object
Examples
# Single cross-validation test with 25% test set
demsup_xvtest_25pct <- dcpo_xvt(demsup_data,
chime = FALSE,
number_of_folds = 4,
iter = 300,
chains = 1) # 1 chain/300 iterations for example only; use defaults
get_xvt_results(demsup_xvtest_25pct)
Extract DCPO Results
Description
summarize_dcpo_results is a convenience function that produces summary statistics of the main parameters of a DCPO stanfit object along with the relevant identifying information (country, year, question, and cutpoint).
Usage
summarize_dcpo_results(
dcpo_input,
dcpo_output,
pars = c("theta", "sigma", "alpha", "beta", "delta"),
probs = c(0.1, 0.9)
)
Arguments
dcpo_input |
the data frame of survey items and marginals generated by |
dcpo_output |
a stanfit object output by |
pars |
a character vector of parameter names to be summarized from the |
probs |
a numeric vector of quantiles of interest; the default is c(.1, .9) |
Value
a tibble
Examples
out1 <- dcpo(demsup_data,
chime = FALSE,
chains = 1,
iter = 300) # 1 chain/300 iterations for example purposes only; use defaults
theta_results <- summarize_dcpo_results(dcpo_input = demsup_data,
dcpo_output = out1,
pars = "theta")