Thanks to both Clive and Richard for clarifying the above subject. To
identify the problem further, I did the following:
I ran -collin- and found several collinear variables. Although these
are not main variables of interest, I included them to control their
effects. Removing them and rerunning the regression made the Wald
Chi-Square even higher.
I managed to identify one variable whose removal made the chi-square
statistic look more reasonable. This is a year dummy variable, included
as a control. Combining this variable with another year dummy produced
more sensible chi-square results.
I also ran the regression without the cluster option. The results gave
me a reasonable chi-square. However, some of the variables that I
controled for did not come out significant.
So, it seems to me that the problem could be due to clustering, or the
inclusion of one particular year dummy variable, or both. I checked
Section 8.3 of Hosmer-Lemeshow book, have exhausted references to
cluster option from the Stata website, and am wondering if someone could
provide me with additional citations to help me learn more about this
subject. Also, what is the relationship between the number of
observations within a cluster and the number of independent variables?
Is there any specific requirement that the former be larger than the
latter, or is this an irrelevant issue?
Thanks,
Daniel Indro
-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Clive
Nicholas
Sent: Saturday, March 11, 2006 8:11 PM
To: [email protected]
Subject: Re: st: Wald Chi-Square in Logistic with Cluster Option
Richard Williams wrote:
> Thanks to Clive for the kind words. Alas, much as I'd like to claim
> credit for -collin- (along with xtabond2 and several other programs!)
> the actual author is Phil Ender and you need to get it from UCLA, not
> SSC. Just use -findit collin- to get a copy.
Whoops! Apologies to Phil Ender...
CLIVE NICHOLAS |t: 0(044)7903 397793
Politics |e: [email protected]
Newcastle University |http://www.ncl.ac.uk/geps
Whereever you go and whatever you do, just remember this. No matter how
many like you, admire you, love you or adore you, the number of people
turning up to your funeral will be largely determined by local weather
conditions.
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