chantrics adjusts the loglikelihood of common econometric models for
clustered data based on the estimation process suggested in
Chandler and Bate (2007),
using the chandwich package,
and provides convenience functions for inference on the adjusted models.
adj_loglik() adjusts the model's parameter covariance matrix to
incorporate clustered data, and can mitigate model misspecification by
wrapping chandwich::adjust_loglik for the supported models.
The returned model of class chantrics can be plugged into standard model
evaluation and model comparison methods, for example, summary(), confint()
and anova(), and a hypothesis test framework provided by alrtest().
See vignette("chantrics-vignette", package = "chantrics") for an
overview of the package.
R. E. Chandler and S. Bate, Inference for clustered data using the independence loglikelihood, Biometrika, 94 (2007), pp. 167–183. doi: 10.1093/biomet/asm015 .