On Wednesday 02 July 2008 16:52:41 Arne Henningsen wrote: > Hi all! > > Do you know if there is any R function/package that can be used to > estimate "tobit" models with panel data (e.g. with random individual > effects)? > > In economics, a "tobit" model is a model with a dependent variable that is > left-censored at zero. Hence, it is a special case of a survival model and > can be estimated using the "survival" package (see e.g. [1]). However, as > far as I know, this package cannot account for a panel structure of the > data (i.e. data with two dimensions: usually time and individuals). > > [1] http://finzi.psych.upenn.edu/R/Rhelp02a/archive/121253.html
On Thursday 03 July 2008 14:27:30 Terry Therneau wrote: > Adding true random effects to survreg is certainly on my list of useful > additions, but one with no start date in sight. That said, one can get > an alternate solution with > survreg(Surv(time, status) ~ x1 + x2 + frailty.gaussian(id, > method='aic')) > > Justification: one can view a random effects model as a penalized > model, that is, as > a. the addition of "factor(id)" - a coefficient b_i for each subject > b. a shrinkage penalty, -.5*k* sum(b_i^2), is added to the log-lik, > and we minimize the sum > c. the value of k is chosen to maximize an integrated likelihood, one > with the b's integrated out. 1/k is the variance of the random effect > > The above code uses the AIC to choose k. You could also use a > user-specified degrees of freedom. > > WARNING: Using "method='reml'" in the above won't work correctly. The > fact that no warning is given in this case is serious flaw in the > survival package. (In my defense, the 'penalty function' code for coxph > and survreg was designed to allow general user-written penalties; a side > effect is that the penalty functions can't easily tell which routine is > calling them. Most, e.g., pspline() and ridge(), work for both coxph and > survreg. But frailty with either an 'ml' or 'reml' argument computes the > appropriate Cox model integral, not the survreg one, and so gives > nonsense answers when used with survreg.) Thanks, Terry, for your detailed answer. I will try this. I did not figure out yet, whether the "bayesSurv" [1] or the "JM" [2] package can be used to estimate tobit models with panel data. Any hints are welcome? [1] http://cran.r-project.org/web/packages/bayesSurv/index.html [2] http://cran.r-project.org/web/packages/JM/index.html Thanks in advance, Arne -- http://www.arne-henningsen.name ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
