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  • urban kim
    started a topic report var(residual) / melogit vs. xtmixed ?

    report var(residual) / melogit vs. xtmixed ?

    l am working about cross-classified multilevel model

    dependent variable : immigration y/n (binary, immigration : 1, none : 0), level1 : personal variable, level2 : move-out reigon(varlist : depid_), level2: move-in region(varlist : arrid_)



    meqrlogit immigration(binary) || all : R.depid_(move-out region) || arrid_(move-in region):, var


    i use "var" option. but, didn't report the result of variance(residual). what's the problem?



    can i use xtmixed model instead of melogit model in binary dependent variable?

  • Weiwen Ng
    replied
    Also, xtmixed is the old name for mixed. Both fit hierarchical linear models. If you fit one to binary data, that's like fitting a fancier linear probability model. Some people will get nervous if you do that, because we do have logistic regression. LPMs actually work fairly well, though.

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  • Clyde Schechter
    replied
    In a logistic model, the residual variance is always pi2/3.

    Leave a comment:

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