R: Hierarchical Ordered Probit Models with Application to Reporting Heterogeneity

# Hierarchical Ordered Probit Models with Application to Reporting Heterogeneity

## Documentation for package ‘hopit’ version 0.11.6

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

## Help Pages

anova.hopit | Likelihood Ratio Test Tables
boot_hopit | Bootstrapping hopit model
disabilityWeights | Standardization of the coefficients
getCutPoints | Calculate the threshold cut-points and individual adjusted responses using Jurges' method
getLevels | Summarize the adjusted and the original self-rated response levels
healthIndex | Calculate the latent index
healthsurvey | Artificially generated health survey data
hopit | Generalized hierarchical ordered threshold models.
hopit.control | Auxiliary for controlling the fitting of a 'hopit' model
latentIndex | Calculate the latent index
percentile_CI | Calculating the confidence intervals of the bootstrapped function using the percentile method
standardiseCoef | Standardization of the coefficients
standardizeCoef | Standardization of the coefficients
svy.varcoef_hopit | Calculation of the variance-covariance matrix for a specified survey design (experimental function)