Re: [R] Use of survreg.distributions

From: Abdus Sattar <>
Date: Fri, 25 Apr 2008 10:02:21 -0700 (PDT)

Hello Dr. Therneau:

Thank you for your response. Let me explain to you want I want. My y variable(time) is normal and would like to fit the model on logarithmic transformation of y (log(y)). I tried to run codes according to your suggestion: tfit=survreg(Surv(y, y>=-5, type="left")~x + cluster(id), dist="lognormal",, scale=0, weights=w)

The following error message is giving:

Error in survreg(Surv(y, y >= -5, type = "left") ~ x +  :
  Invalid survival times for this distribution
In addition: Warning messages:

1: In log(dlist$dtrans(Y[exactsurv, 1])) : NaNs produced 2: In log(y) : NaNs produced

Note, the data file does not contain any missing data! Do you know why it is giving me such an error message please? Thank you again for your helpful comment/suggestion.

Best Regards,

Abdus Sattar

--begin included message ---

I am using survreg(Surv()) for fitting a Tobit model of left-censored longitudinal data. For logarithmic transformation of y data, I am trying use survreg.distributions in the following way: tfit=survreg(Surv(y, y>=-5, type="left")~x + cluster(id), dist="gaussian",, scale=0, weights=w)


tfit=survreg(Surv(y, y>=-5, type="left")~x + cluster(id), dist=my.gaussian,, scale=0, weights=w)

If I run these codes then I got the following error message,

Error in survreg(Surv(y, y >= -5, type = "left") ~ x +  : Invalid distribution object

Does anybody can help me in identifying the error(s) in these code please?

  Can you tell us what you are trying to do? 
  Your first model was a fit of y ~ x + eps, eps ~ Gaussian.  If what you want
is log(y) ~ x + eps, then all that you need do is use dist="loggaussian" in the survreg call.  (Or 'lognormal'; which is the same distribution.)
      Terry Therneau

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