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st: RE: Detecting serial correlation in panel dataset with a binary dependent variable


From   "Nick Cox" <n.j.cox@durham.ac.uk>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: RE: Detecting serial correlation in panel dataset with a binary dependent variable
Date   Mon, 30 Oct 2006 17:42:38 -0000

Binary or not, autocorrelations are still defined. 
I would expect the standard graphs still to make much 
sense, but P-values to make less sense, although my 
recollection is that the standard errors of autocorrelations
are not that sensitive to the marginal distribution of the
process. A plot of the response against 
lagged response will just be four blobs unless you -jitter()-.
But a 2 X 2 table might then be a good summary. 

Nick 
n.j.cox@durham.ac.uk 

Johan Hellström
 
> I have an unbalanced time-series-cross-sectional dataset with a binary
> dependent variable. I would like to find a way for detecting 
> autocorrelation
> in the model. However, as the sample is rather small (about 
> 160) and the
> time-series unit is about 10-15 it would probably be unwise to use
> statistical tests on time dummy variables to detect temporal 
> dependence (as
> the loss of degrees of freedom would affect the efficiency of 
> these tests).
> 
> Does anyone have an alternative solution for this problem 
> (i.e. detecting
> temporal dependence in an unbalanced TSCS-data set with a 
> limited dependent
> variable)?

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