I add an example , all the variables are mutually excluding dummy variables, notice the different intercept: 5.627 vs 5.545: survreg: Value Std. Error z p (Intercept) 5.627 0.00887 634.3 0.00e+00 Var1.recR2 -0.108 0.01026 -10.5 1.00e-25 Var1.recR3 -0.490 0.01099 -44.5 0.00e+00 Var1.recR4 -0.542 0.01303 -41.6 0.00e+00 Var1.recR5 -0.891 0.01095 -81.3 0.00e+00 Log(scale) -0.324 0.00350 -92.7 0.00e+00
Scale= 0.723 Log logistic distribution Loglik(model)= -379503.5 Loglik(intercept only)= -383388.9 Chisq= 7770.76 on 4 degrees of freedom, p= 0 aftreg: Covariate W.mean Coef Exp(Coef) se(Coef) Wald p Var1.recR 1 0.253 0 1 (reference) 2 0.330 0.108 1.114 0.010 0.000 3 0.191 0.490 1.632 0.011 0.000 4 0.106 0.542 1.720 0.013 0.000 5 0.120 0.891 2.437 0.011 0.000 log(scale) 5.545 256.029 0.008 0.000 log(shape) 0.324 1.383 0.003 0.000 Max. log. likelihood -379504 -- View this message in context: http://r.789695.n4.nabble.com/aftreg-vs-survreg-loglogistic-aft-model-different-intercept-term-tp3059250p3060545.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org 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.