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     Â
z       p
sexom           -0.2187    0.0993 -2.202 2.76e-02
and the log rank result
>Â 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 458Â Â Â Â Â 458Â Â Â Â Â 472Â Â Â Â 0.397Â Â Â Â Â 1.83
sexo=m 451Â Â Â Â Â 451Â Â Â Â Â 437Â Â Â Â 0.428Â Â Â Â Â 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]
Para: mariaeugeniau
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 Â 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. Â (The same answer applies to ordinary linear regression.)
2. You have not given us enough information to answer the questions. Â If
the data is p=.049 vs p=.051, the the answers are in agreement even
though the artificial label of "significant" changes. Â The logrank test
and survreg are not the same model. Â If the data is p=.02 vs p=.8, then
you have an error in the code.
Terry Therneau
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