R: Progression Models for Repeated Measures

# Progression Models for Repeated Measures

## Documentation for package ‘pmrm’ version 0.0.4

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

## Help Pages

AIC.pmrm_fit | Akaike information criterion (AIC)
BIC.pmrm_fit | Bayesian information criterion (BIC)
coef.pmrm_fit | Treatment effect parameters
confint.pmrm_fit | Confidence intervals of parameters
deviance.pmrm_fit | Deviance
fitted.pmrm_fit | Fitted values
glance.pmrm_fit | Glance at a PMRM.
logLik.pmrm_fit | Extract the log likelihood.
plot.pmrm_fit | Plot a fitted PMRM.
pmrm_estimates | Parameter estimates and confidence intervals
pmrm_marginals | Marginal means
pmrm_model_decline_nonproportional | Fit the non-proportional decline model.
pmrm_model_decline_proportional | Fit the proportional decline model.
pmrm_model_slowing_nonproportional | Fit the non-proportional slowing model.
pmrm_model_slowing_proportional | Fit the proportional slowing model.
pmrm_simulate_decline_nonproportional | Simulate non-proportional decline model.
pmrm_simulate_decline_proportional | Simulate proportional decline model.
pmrm_simulate_slowing_nonproportional | Simulate non-proportional slowing model.
pmrm_simulate_slowing_proportional | Simulate proportional slowing model.
predict.pmrm_fit | Predict new outcomes
print.pmrm_fit | Print a fitted PMRM.
residuals.pmrm_fit | 'pmrm' residuals.
summary.pmrm_fit | Summarize a PMRM.
tidy.pmrm_fit | Tidy a fitted PMRM.
VarCorr.pmrm_fit | Estimated covariance matrix
vcov.pmrm_fit | Treatment effect parameter covariance matrix