Changelog
Source:NEWS.md
eventglm 1.4.5
Bug fixes:
- Binder IPCW method was not being calculated correctly. It could have impacted the intercept (and hence predictions), but coefficient estimates have always been consistent. Now predictions and the intercept should also work correctly. (Thanks @alexpate30)
eventglm 1.4.4
Bug fixes:
- Handle cases where last observation is an event leading to NaN (thanks @trinhdhk)
eventglm 1.4.0
New features:
- New pseudo module for infinitesimal jackknife that allows for delayed entry/left truncation.
eventglm 1.3.0
New features:
- Allow id argument in cumincglm and rmeanglm. When id is present, geese.fit will be used instead of glm.fit, with clusters indicated by the id. This is to account for clustered data, for example.
- Informative error message if there is missing data in the censoring model
eventglm 1.2.0
New features:
Time vector allowed in cumincglm. Use this to model multiple timepoints simultaneously, and allow for time varying covariate effects using tve() (for time varying effect) in the right side of the formula. Inverse probability of censoring weights are returned by the fitting functions in the list element called “ipcw.weights”. * Small edits and improvements to the documentation.
eventglm 1.1.1
Bug fixes:
- Check and fix name clashes for reserved variables pseudo.vals, .Tci, and .Ci
- Minor efficiency updates in corrected covariance estimation
- Improve documentation
eventglm 1.1.0
New features and vignette:
- Methods for computing pseudo observations are now in modules.
- Users can define their own modules for computing pseudo observations
- Option to use survival instead of cumulative incidence in standard models