Re: [R] Power analysis

Agree with Greg's point. In fact it does not make logical sense in many cases. Similar to the use of the "statistically unreliable" reliability measure Cronbach's alpha in some non-statistical fields. -- View this message in context: http://r.789695.n4.nabble.com/Power-analysis-tp2524729p2524907

Re: [R] Question regarding significance of a covariate in a coxme survival

What statistical measure(s) tend to be answering ALL(?) question of practical interest? -- View this message in context: http://r.789695.n4.nabble.com/Re-Question-regarding-significance-of-a-covariate-in-a-coxme-survival-tp2399386p2399577.html Sent from the R help mailing list archive at Nabbl

Re: [R] Question regarding significance of a covariate in a coxme survival model

My suggestion for Teresa: If compare model 1 and model 2 with model 0 respectively, the (penalized) likelihood ratio test is valid. IF you compare model 2 with model 3, the (penalized) likelihood ratio test is invalid. You may want to use AIC/SBC to make a subjective decision. -- View this

Re: [R] Question regarding significance of a covariate in a coxme survival model

The likelihood ratio test is more reliable when one model is nested in the other. This true for your case. AIC/SBC are usually used when two models are in a hiearchical structure. Please also note that any decision made made based on AIC/SBC scores are very subjective since no sampling distributi