R: Interface for Multilevel Regression and Poststratification

# Interface for Multilevel Regression and Poststratification

## Documentation for package ‘shinymrp’ version 0.10.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

check_estimate_exists | Check if poststratification has been performed
check_fit_exists | Check if model has been fitted
compare_models | Compare models using LOO-CV
covar_hist | Create geographic covariate distribution histogram
create_model | Create a new MRPModel object
demo_bars | Create demographic comparison bar plots
diagnostics | Return sampling diagnostics
estimate_map | Create a choropleth map of MRP estimates
estimate_plot | Visualize estimates for demographic groups
example_model | Return example 'MRPModel' object with estimation results.
example_pstrat_data | Return example poststratification data
example_sample_data | Return example data
fit | Fit multilevel regression model using cmdstanr
formula | Return model formula
link_acs | Link sample data to ACS data
load_pstrat | Load custom poststratification data
log_lik | Create inputs for leave-one-out cross-validation
metadata | Return model metadata.
model_spec | Return model specification
MRPModel | MRPModel objects
MRPModel-method-check_estimate_exists | Check if poststratification has been performed
MRPModel-method-check_fit_exists | Check if model has been fitted
MRPModel-method-diagnostics | Return sampling diagnostics
MRPModel-method-fit | Fit multilevel regression model using cmdstanr
MRPModel-method-formula | Return model formula
MRPModel-method-log_lik | Create inputs for leave-one-out cross-validation
MRPModel-method-metadata | Return model metadata.
MRPModel-method-model_spec | Return model specification
MRPModel-method-poststratify | Run poststratification to generate population estimates
MRPModel-method-ppc | Create input for posterior predictive check
MRPModel-method-save | Save model object to file
MRPModel-method-stan_code | Return model Stan code.
MRPModel-method-summary | Return posterior summary table
MRPWorkflow | MRPWorkflow objects
MRPWorkflow-method-compare_models | Compare models using LOO-CV
MRPWorkflow-method-covar_hist | Create geographic covariate distribution histogram
MRPWorkflow-method-create_model | Create a new MRPModel object
MRPWorkflow-method-demo_bars | Create demographic comparison bar plots
MRPWorkflow-method-estimate_map | Create a choropleth map of MRP estimates
MRPWorkflow-method-estimate_plot | Visualize estimates for demographic groups
MRPWorkflow-method-link_acs | Link sample data to ACS data
MRPWorkflow-method-load_pstrat | Load custom poststratification data
MRPWorkflow-method-outcome_map | Visualize raw outcome measure by geography
MRPWorkflow-method-outcome_plot | Create summary plots of the outcome measure
MRPWorkflow-method-pp_check | Perform posterior predictive check
MRPWorkflow-method-preprocess | Preprocess sample data
MRPWorkflow-method-preprocessed_data | Return preprocessed sample data
MRPWorkflow-method-sample_size_map | Create sample size map
mrp_workflow | Create a new MRPWorkflow object
outcome_map | Visualize raw outcome measure by geography
outcome_plot | Create summary plots of the outcome measure
poststratify | Run poststratification to generate population estimates
ppc | Create input for posterior predictive check
pp_check | Perform posterior predictive check
preprocess | Preprocess sample data
preprocessed_data | Return preprocessed sample data
run_app | Run the Shiny Application
sample_size_map | Create sample size map
save | Save model object to file
stan_code | Return model Stan code.
summary | Return posterior summary table