Dear List,
In documents (Therneau, 2003 : On mixed-effect cox models, ...), as far as I came to know, coxme penalize the partial likelihood (Ripatti, Palmgren, 2000) where as frailtyPenal (in frailtypack package) uses the penalized the full likelihood approach (Rondeau et al, 2003). How, then, coxme and coxph(...frailty(id, dist='gauss')) differs? Just the coding algorithm, or in approach too? coxph(...frailty(id, dist='gamma')) estimates by means of the penalized likelihood approach (Hougaard, 2000). Same for coxph(...frailty(id, dist='gauss'))? How these are related with nltm(...model="GFT") in nltm package done in the approach of Non-linear transformation (Tsodikov, 2003)? Also, is the 3 stage approach (Hougaard, 2000, pp.267) implimented anywhere in R? Finally, Is there a R version of the Frailty.stable (A set of Splus function to estimate parameters of a positive stable frailty model) by Wassell et al (1999)? Thanks for your valuable time. Thanks in advance. Mohammad Ehsanul Karim Institute of Statistical Research and Training, University of Dhaka ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
