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Thread: Missing Data

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    Missing Data




    Hi All,

    I am running a number of mulitple regression analyses and wanted to know how to use Little's MCAR test to assess missing data.

    Specifically, do you run a separate Little MCAR test for each regression (i.e., those variables in each separate regression), or do I run on Little MCAR test on the whole data set?

    Thanks!

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    Re: Missing Data


    It has been about four years since I used the test, so accept my post with caution. It probably depends on how the test is set-up, but If I remember correctly, you don't list the dependent variables or independent variables implicitly in the test - it just looks for any general patterns. So if that is so, then I think it provides a global result. Thus meaning no discernible pattern. If so, you probably don't need to run it a bunch of times. An issue with just running it with all variable once, could be that it finds a pattern in variables not in the models you are interested in. Say antecedents to variables of interest, etc. I also, don't know the power of the test. So with sparse data you could (just guessing) get a non-significant pvalue due to small sample size, but there is a possible concern for MCAR.


    Lastly, this below post link covers my other comments and recommendations. Side note, logistic regression is a good approach, though it could also have the same power issues as Little's test.


    https://stats.stackexchange.com/ques...tles-mcar-test
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