05-14-2013 03:41 PM
I'm trying to use some form of survival analysis (e.g. accelerated failure time or proportional hazards) to study seed germination time. My data is interval censored (also called "grouped-time") and has a random effect (also called "frailty"). How can I do this in SAS?
My seeds were on petri dishes that were censused on day 1, 3, 5, 8, and 14. These are interval censored, with a seed that germinated on d8 really germinated between day 6 and day 8. PROC LIFEREG can handle interval censoring, but as far as i know, it doesn't handle random effects. Seeds on the same petri dish are not independent, so I need to be able to include the dish as a random effect.
Is there an approach that allows interval censoring as well as random effects? If so , how should I modify the SAS code below to include random effects? Will I need a more general procedure like PROC NLMIXED? What is the best/easiest way to do this?
PROC LIFEREG DATA=survGeno2 plots=probplot;
TITLE "Interval censored AFT";
/*how do i include a petri dish random effect?*/
02-04-2014 12:28 PM
You can do so by introducing a 'random' statement in a proc phreg I reckon, the code will be:
(proc phreg can also handle interval timing)
proc phreg data=survGeno2 ;
with status=1 if the seed germinated and 0 if it didn't /censored
02-04-2014 03:40 PM
Phreg can't be used to analyse intervalcensored data in general. Phreg can handle lefttruncated data as specified by fabie10, but lefttruncated data is not the same as intervalcensoring. Though, If the structure of your data is simple enough, then the interval censored data can be analysed as tied data, which can be analyzed with ties=discrete in phreg.
In the very newest version there is this proc iclifetest available, which can anlyse interval-censored data. I haven't tried it, but I don't think it allow fra a random effect.
There is also the possibility of using proc nlmixed. There you can specify a any likelyhoodfunction and use the random effects. There is a good example of how to specify a right-censored frailty mdel in the examples in the sas-help section. This method can also be used when data are interval censored. The draw-back of this method is that you need a very detailed knowledge of how your likelihood function is constructed, since you have to specify it yourself.