Posted by
Poes, Matthew Joseph on
Feb 16, 2012; 2:15pm
URL: http://spssx-discussion.165.s1.nabble.com/Weighting-in-GENLINMIXED-tp5489150p5489845.html
A weighted sample needs to be analyzed as a weighted sample. Otherwise your standard errors will be wrong (inflated), and your significance tests may not be accurately interpretable. It's especially important in MLM/HLM procedures because of how variance is partialed out. However, having said that, I don't know how to do that in SPSS without the advanced sampling package. I personally use SAS for most of my multi-level modeling, and again, I'm not sure how to handle complex samples with SAS and MLM, so I've had to use HLM for such a procedure. In other words, I believe you may not be able to handle this correctly with SPSS. Even if they did have the necessary feature with the advanced sampling add-on (someone from SPSS might need to answer that), you would have to find out what approach it uses in multi-level modeling. In general, with any form of hierarchical model, a different form of multi-stage weighting is suggested from the more traditional approaches.
-Matt
-----Original Message-----
From: SPSSX(r) Discussion [mailto:
[hidden email]] On Behalf Of Hector Maletta
Sent: Thursday, February 16, 2012 4:28 AM
To:
[hidden email]
Subject: Weighting in GENLINMIXED
I am asked to assist in an application of a multilevel model through GENLINMIXED, for a survey based on a three-stage clustered sample (first selecting towns, then neighborhoods, then households). Since the multilevel model would look for effects within and between towns, neighborhoods in towns, and households in towns and neighborhoods, the question is what to do in this case about sample weighting.
For other analyses (including tabulations of results) each household is weighted according to the product of the reciprocals of sampling ratios at the three stages (Pt/St)(Ptn/Stn)(Ptnh/Stnh) where M=Population and S=sample, t=towns, n=neighborhoods, and h=households. These weights, in this format, correct for proportionality of sampling, and also inflate the weighted sample to population size. A deflation of the weighted sample to its original sample size could be achieved through multiplying those weights by the ratio R=(total household sample size/total households in the population).
The question is whether any weight (inflationary or most probably not inflationary) should be used when analyzing a multilevel model where the levels are the sampling stages. I have heard opinions for and against, and would like to hear more on the subject.
Hector
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