Dear Terry  here is the survreg line from which I understand that "gender" is significant
survreg(formula = Surv(dias, status) ~ trat * sexo * rep, dist = "weibull")                   Value    Std. Error      z       p sexom           -0.2187    0.0993 -2.202 2.76e-02 and the log rank result > survdiff(Surv(dias, status) ~ sexo) Call: survdiff(formula = Surv(dias, status) ~ sexo)         N Observed Expected (O-E)^2/E (O-E)^2/V sexo=h 458     458     472    0.397     1.83 sexo=m 451     451     437    0.428     1.83  Chisq= 1.8 on 1 degrees of freedom, p= 0.176 do you think this could be an error code or is it because they are different models? thank you very much Eugenia ________________________________ De: Terry Therneau-2 [via R] <ml-node+s789695n4551787...@n4.nabble.com> Para: mariaeugeniau <mariaeugen...@yahoo.com.ar> Enviado: jueves, 12 de abril de 2012 10:06 Asunto: Re: Survreg output - interpretation --- begin included message --- Hello R users, I am analizing survival data (mostly uncensored) and want to extract the most out of it. Since I have more than one factor, I?ve read that the survival regression can help to test the interactions between factors, and then decide how to do the comparisons using the Log-rank test (survdiff). 1- if I chose the Weibull distribution, does the output inform the goodness of fit to it? perhaps in this part of the output... Weibull distribution Loglik(model)= -1302.8  Loglik(intercept only)= -1311      Chisq= 16.49 on 11 degrees of freedom, p= 0.12 Number of Newton-Raphson Iterations: 7 n= 873 2- one of my factors is "gender" (2 levels). With survreg, it appears as significant, but if I compare them with log-rank it turns not significant. Are they comparing different things? or is it a test power issue? ------- end inclusion ------- 1. To understand goodness of fit you need to look at the residuals in multiple ways.  (The same answer applies to ordinary linear regression.) 2. You have not given us enough information to answer the questions.  If the data is p=.049 vs p=.051, the the answers are in agreement even though the artificial label of "significant" changes.  The logrank test and survreg are not the same model.  If the data is p=.02 vs p=.8, then you have an error in the code. Terry Therneau ______________________________________________ [hidden email] 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. ________________________________ If you reply to this email, your message will be added to the discussion below:http://r.789695.n4.nabble.com/Survreg-output-interpretation-tp4549368p4551787.html To unsubscribe from Survreg output - interpretation, click here. NAML -- View this message in context: http://r.789695.n4.nabble.com/Survreg-output-interpretation-tp4549368p4552481.html Sent from the R help mailing list archive at Nabble.com. [[alternative HTML version deleted]]
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