Split-Population Duration (Cure) Regression
Accessor methods for spdur Objects
Add duration variables to panel data
AIC method for spdur
Convert spdur results to summary data frame
Attempt to convert to R date format
BIC method for spdur
Expand call to full names.
Forecast from a spdur model
Calculate hazard function values
Regular Log-logistic regression
Regular Log-logistic likelihood
Lag panel data
Plot split-duration model results.
Plot hazard function
Plot conditional hazard rate
Simulate and plot hazard function
Predict methods for spdur Objects
Print a split-population duration model results summary
Generate a Separation Plot
Split-population duration (cure) regression
Split-Population Duration (Cure) Regression Models
Split-population Log-logistic regression
Split-population Log-logistic log likelihood
Split-population Weibull log likelihood
Split-population Weibull regression
Summarize split-population duration results
Regular weibull log likelihood
Regular Weibull regression
Create export table for a split-duration model
An implementation of split-population duration regression models. Unlike regular duration models, split-population duration models are mixture models that accommodate the presence of a sub-population that is not at risk for failure, e.g. cancer patients who have been cured by treatment. This package implements Weibull and Loglogistic forms for the duration component, and focuses on data with time-varying covariates. These models were originally formulated in Boag (1949) and Berkson and Gage (1952), and extended in Schmidt and Witte (1989).
Useful links