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Interval censored Data in survreg() with zero values!

3 messages · Geraldine Henningsen, Don MacQueen, Achim Zeileis

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Hello,

I have interval censored data, censored between (0, 100). I used the
tobit function in the AER package which in turn backs on survreg. 
Actually I'm struggling with the distribution. Data is asymmetrically
distributed, so first choice would be a Weibull distribution. 
Unfortunately  the Weibull doesn't allow for zero values in time data,
as it requires x > 0. So I tried the exponential distribution that
allows x to be >= 0 and the log-normal that sets x <= 0 to 0. Still I
get the same error:

"     Fehler in survreg(formula = Surv(ifelse(A16_1_1 >= 100, 100,
ifelse(A16_1_1 <=  :
  Invalid survival times for this distribution "

The only distributions that seem to work are gaussian and logistic, but
they don't really fit the data. 
I searched for this problem in the archive and found a suggestion by
Terry Therneau to set all 0  to NA, applying Weibull afterwards.  But
this solution is not very satisfying as it eliminates the left censored
data from the dataset.

So I have three questions:

1. Does anybody know why the lognormal and exponential distribution
don't work in survreg?

2.  What else could I do to find a distribution that fits the data well?

3. What about the non-parametric approach in survfit(), could that be a
solution?

I hope my question aren't too stupid, as I'm not a big statistician.

Regards,

Geraldine
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Surv() allows left, right, or interval censoring.

Try left censoring instead of interval censoring. For the weibull or 
lognormal, think of your data as <=100 instead of [0,100].

-Don
At 8:08 PM +0100 12/23/08, Geraldine Henningsen wrote:

  
    
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On Tue, 23 Dec 2008, Geraldine Henningsen wrote:

            
For these distributions, observations left-censored at zero are rather 
unlikely to occur: pexp(0) = plnorm(0) = 0.
Both probably depend on the questions you want to ask about your data. For 
the tools implemented in "survival", the "Modeling Survival Data" book by 
Therneau and Grambsch is the natural reference.

hth,
Z