Likelihood Ratio Tests for Multiply Imputed Datasets: Introducing milrtest
Through the use of user-written programs, primarily mim (Carlin, Galati, and Royston, 2008), Stata users can analyze multiply imputed (MI) datasets. Among other capabilities, mim allows the user to estimate a range of regression models and to perform a multi-parameter hypothesis tests after model estimation using a Wald test. The program presented here allows the user to perform likelihood ratio tests on models using multiply imputed datasets after mim. This provides an additional means of testing nested models after estimation using MI data. The process used to perform the likelihood ratio tests is described in Meng and Rubin (1992). The test statistic is calculated based on two sets of likelihood ratio tests. The first involves calculating the likelihood ratio for the null versus alternative hypothesis in each of the m imputed datasets. The second involves calculating the likelihood for the null and alternative hypotheses in each of the m datasets, constraining the parameters to be the estimates based on combining coefficient estimates from the m datasets (i.e. the average of the parameter estimates across the m imputed datasets). The current version allows testing for a limited number of regression commands (i.e. regression, logit, and ologit), but subsequent versions may include compatibility with additional commands.
|Date of creation:||16 Nov 2008|
|Date of revision:|
|Contact details of provider:|| Web page: http://stata.com/meeting/fnasug08/|
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:boc:fsug08:11. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F Baum)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.