[R] mixed-effects models for left-censored data?

[Thomas Lumley]

On Wed, 11 Jun 2003, Remko Duursma wrote:

> Dear R-helpers,
>
> excuse me if this is not exclusively an R-related question.
>
> I have data from a nested design, both temporally and spatially, and the
> reponse variable of interest is left-censored. That is, only values >
> "some treshold" are available, otherwise "LOW" is reported.
>
> Are there ways of building a linear model with both fixed and random
> effects, when the response variable is censored? Can the tobit model be
> modified to do this? Does anyone have experience with this type of
> dataset?
>

For a random intercept model you could use survreg() and frailty() in the
survival package.

In general the random effects tobit model will be quite hard to fit,
involving a numerical integration whose dimension is the number of random
effects.   Some sort of EM algorithm might work.

There is a paper by Pettit in Biometrics some time ago on censored linear
mixed models -- I don't have the reference with me.

	-thomas