[R] Logit Regressions, Clustering etc

[Paul Sweeting]

Fantastic - I new it would be straightforward if I could only find the
function!

Many thanks

Paul

-----Original Message-----
From: Frank E Harrell Jr [mailto:f.harrell at vanderbilt.edu] 
Sent: 29 January 2008 20:30
To: Paul Sweeting
Cc: r-help at r-project.org
Subject: Re: [R] Logit Regressions, Clustering etc

Paul Sweeting wrote:
> 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

library(Design)
f <- lrm(Y ~ x1 + x2 + ..., x=TRUE, y=TRUE)
g <- robcov(f, subjectID)
anova(g)
summary(g)
etc.

Frank

> 
> 
>> 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, I’ve 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.
> 
>> ______________________________________________
>> R-help at 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.
> 
> ______________________________________________
> R-help at 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.
> 


-- 
Frank E Harrell Jr   Professor and Chair           School of Medicine
                      Department of Biostatistics   Vanderbilt University