Interface for Multilevel Regression and Poststratification

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Documentation for package ‘shinymrp’ version 0.9.0

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

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