[R] Logit Regressions, Clustering etc
Paul Sweeting
mail at paulsweeting.co.uk
Tue Jan 29 18:42:00 CET 2008
Hi
Sorry to bother the list again, but no-one has so far been able to suggest
any help for the query below. As an added incentive, I have been asked "why
don't you do this in Stata? It's just a case of adding a flag in the
regression..."
I'm loathe to start learning another stats package, so if anyone is able to
help...!
Thanks
Paul
>Hi
>I am carrying out some logit regressions and want to (a) make sure I'm
>taking the right approach and (b) work out how to carry out some additional
>analysis. So, to carry out a logit regression where the dependent variable
>is a factor db, I use something like:
>res1_l <- glm(formula = db ~ y1 +
+ y5, family = binomial(link =
"logit"))
>summary(res1_l)
>...which is, I hope correct. I also need to carry out an ordered logit
>regression. Is this as simple as:
>res1_l <- polr(formula = db ~ y1 +
+ y5)
>summary(res1_l)
>..with db being a factor which has more levels than just "0" and "1"?
>Assuming it is, the part I am really struggling with is the calculation of
>robust standard errors to allow for clustering. In an "ordinary"
>regression, Ive used survreg, where the data has also been censored, e.g.:
>res1 <- survreg(formula = Surv(ip, db_Censor) ~ y1 +
y5 + cluster(db_ID),
>dist = "gaussian")
>summary(res1)
>This has the benefit of giving a nice clear display of the naïve standard
>error as well as the robust one - is there any way of getting similar
output
>for a logit and an ordered logit regression
>Thanks in advance for your help.
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