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Thread: Interaction test

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    Re: Interaction test




    Sorry for all of the posts. See following for relevant reading:


    http://www.pharmasug.org/proceedings...-2014-HA09.pdf
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    Re: Interaction test

    Thanks for that link.

    If I have 15% missing data for a categorical covariate in a multivariable modified Poisson model (using similar proc genmod code as before), and I make a missing category level within the variable, is there anything I should be aware of, given that I'm using GEEs with the repeated subject statement, and would there be different implications of doing this if the data is missing completely at random versus missing at random?

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    Re: Interaction test

    First off I am guessing you are using the following, correct?


    http://wuss.org/Proceedings13/81_Paper.pdf


    Second here is a description that probably holds for the use a chi-square distribution in your estimate statement:


    https://support.sas.com/documentatio...od_sect035.htm
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    Re: Interaction test

    As for missing data, do you know the missingness mechanism. if data are MCAR, do nothing, MAR, imputation is the best option, NMCAR, there is nothing you can do.


    15% is fairly substantial. How big is your effect size, is it large enough to imagine that it may overshadow 15% systematic loss of data?
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    Re: Interaction test


    In that first link, the outputs are very similar in terms of table formatting, and suggests that Wald CI's and Wald chi-square values are calculated by default. But in the second link you posted, I think it suggests that you actually need to specify Wald option to produce Wald statistics (unless Wald statistics constitute some additional stats apart from the CI's and chi square value).

    For my missing data, the relative measure is about 1.3 (p<0.05) for the non-missing levels of the variable (for the adjusted and unadjusted models), and I think the missing category relative measure changes direction and crosses the null in when comparing its unadjusted vs adjusted value, but I'm not trying to interpret that missing category heavily with a high degree of confidence.

    When you say imputation for MAR, do you mean multiple imputation? b/c I think mode imputation would introduce a lot of bias b/c we have no basis on which we can determine what level of the variable missing values belong to.

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