Dear R help, ## Example from http://stat.ethz.ch/R-manual/R-patched/library/survival/html/frailty.html # Random institutional effect coxph(Surv(time, status) ~ age + frailty(inst, df=4), lung) I am trying to understand what exactly happens when method=df is used ? The R documentation pages says that if /df/ is used then the degrees of freedom for random effects is fixed to that number. I have few questions regarding this 1) How do I specify the correct df? Is it simply any number that leads to model convergence? Is there any sensible way to specify this? Dr. Terry Therneau once said that he chose the df=4 out of nowhere, just like that for this example. https://stat.ethz.ch/pipermail/r-devel/2012-April/063883.html 2) My main question is regarding the methods. What exactly the method=df is doing? I tried to search the vignette but there were very limited details. Does using method=df fixes the scale parameter of my frailty distribution? 3) Finally, a practical question. I am trying to fit a frailty model that have convergence problem. When I use method=df option and adjust the degrees of freedom then it leads to model convergence which otherwise was not possible to achieve? Is it statistically correct to use this option of method=df where I fix the df to a certain number so that my model converges? Suggestions (and criticisms :) ) are all welcome. Thank you very much. Regards, D -- View this message in context: http://r.789695.n4.nabble.com/R-coxph-Method-df-Question-on-methods-tp4640841.html Sent from the R help mailing list archive at Nabble.com.