Hi Chris et al.
Is it possible to advocate for additions and prioritization for your (probably big) to-do list?
1. First and foremost, which should not be too difficult to implement: Selecting variables which are a set of plausible values (this exists in PISA, TIMSS, PIRLS, etc). The quick and dirty solution would be to clarify how the Master imputation file is specified, as in Mplus, so the user could do it her/himself. But that would be unnecessarily clumsy in my opinion.
2. Complex survey stratification: Sometimes using the stratification variable in a fixed effect transformation for model-based inference is just impossible with hundreds or more strata. Mplus incorporate stratification as a an almost invisble variable (it's magic, I'm not asking what's going on behind the curtain!).
Cheers
Stephan
Plausible values and complex survey design
Re: Plausible values and complex survey design
In case others are having challenge#1 above, the pv module in Stata can be used with runmlwin. With some minor tweaks to the pv ado file it works like a charm.
Code: Select all
pv, pv(SCI*) pv1(MAT*): runmlwin @pv @1pv cons SEX AGE SES, level3(SCHOOLID: cons) level2(CLASSID: cons) level1(STUDID: cons) nopause batch nogroup
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Re: Plausible values and complex survey design
Hi Stephan
I tried to apply the command but found some errors. as you mention before: "With some minor tweaks to the pv ado file..." how is exactly to do this?
thanks
I tried to apply the command but found some errors. as you mention before: "With some minor tweaks to the pv ado file..." how is exactly to do this?
thanks