Bookmark and Share

Notice: On March 31, it was announced that Statalist is moving from an email list to a forum. The old list will shut down at the end of May, and its replacement, statalist.org is already up and running.


[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

st: Adjustment to likehood value due to dependence of data observations


From   "Abdul Q Memon" <a.memon@ucl.ac.uk>
To   statalist@hsphsun2.harvard.edu
Subject   st: Adjustment to likehood value due to dependence of data observations
Date   Thu, 22 Sep 2011 15:10:48 +0100

Dear All

I would really appreciate your reply on this.

I have run several models using glm (possion and negative binomial)
command in STATA. Based on the log-likelihood and BIC values I have
selected the most appropriate models (with smallest BIC values). After
this I have run GEE with AR1 structure for only the preferred model to
account for serial correlation in data. I have these two questions.

1. Since my model seclection is based on (log-likelihood and BIC values)
and in this case data is not independent (time series and panel data), is
there a way in stata to adjust the likelihood after running glm command if
the data is not independent.

2. After running gee command still there is some trend in residuals. Do i
need to run robust command to adjust standard errors after gee?? my
understanding is robust command is for corrections to standard error after
OLS.

Many thanks

Memon



*
*   For searches and help try:
*   http://www.stata.com/help.cgi?search
*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/


© Copyright 1996–2014 StataCorp LP   |   Terms of use   |   Privacy   |   Contact us   |   Site index