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 on April 23, and its replacement, is already up and running.

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

st: goodness-of-fit stats with MI data

From   Ryan Wells <>
To   "" <>
Subject   st: goodness-of-fit stats with MI data
Date   Fri, 15 Mar 2013 06:09:00 -0700 (PDT)

I am trying to figure out how to conduct a relevant 
goodness-of-fit test(s) in Stata after conducting a logistic regression 
model for a multiply imputed dataset.

White, Royston and Wood (2011) say that goodness-of-fit test statistics 
should not be combined using Rubin's rules. I know about the Wald-like 
"mi test" Stata command, as well as the implementation of R-squared for regression analysis (following Harel, 2009) in the ssc-downloadable command mibeta. I am also aware that there are proposed alternatives (not using Rubin's standard pooling rules) for a pooled likelihood ratio test statistic and a pooled chi-square test 
statistic (with associated p-values) that are applicable in a multiply 
imputed framework, although to my knowledge these are not implemented in Stata. (If there is a user command for these somewhere, I'd like to 
hear about it.) In my application (analyzing ELS education data from 
NCES), I would have used a BIC or AIC in a non-imputed setting.

What is the recommended procedure to conduct and report a model 
goodness-of-fit test for logistic regression analysis when using mi data in Stata? Thanks.

*   For searches and help try:

© Copyright 1996–2016 StataCorp LP   |   Terms of use   |   Privacy   |   Contact us   |   Site index