- Current version:
1.1.0
- Release date:
19jul2017
penlogit
estimates penalized logistic regression models for a binary response via data augmentation. It allows the user to impose Normal and
generalized log-F prior distributions on one or more model parameters (log odds-ratios).
To install the last version of penlogit
from GitHub, type
net install penlogit, from("https://raw.githubusercontent.com/anddis/penlogit/master/")
from within a web-aware Stata.
Andrea Discacciati and Nicola Orsini (Karolinska Institutet, Stockholm, Sweden)
Sander Greenland (University of California, Los Angeles, CA)
Andrea Discacciati, Nicola Orsini, and Sander Greenland. Approximate Bayesian logistic regression via penalized likelihood by data augmentation. The Stata Journal 2015; 15(3):712–736