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Activity Number:
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316
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Type:
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Invited
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Date/Time:
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Tuesday, August 8, 2006 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Survey Research Methods
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| Abstract - #304969 |
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Title:
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Adjusting for Unequal Selection Probability in Multilevel Models: a Comparison of Software Packages
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Author(s):
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Kim Chantala*+ and C. M. Suchindran
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Companies:
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The University of North Carolina at Chapel Hill and The University of North Carolina at Chapel Hill
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Address:
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Carolina Population Center, University Square, CB #8120, Chapel Hill, NC, 27516-3997,
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Keywords:
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multilevel models ; sample weights ; software
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Abstract:
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Most surveys collect data using complex sampling plans that involve selecting both clusters and individuals with unequal probability of selection. Research in using multilevel modeling techniques to analyze such data is relatively new. Often, sampling weights based on probabilities of selecting individuals are used to estimate population-based models. However, sampling weights used for estimating multilevel models (MLM) need to be constructed differently than weights used for population-average models. This paper compares the capabilities of MLwiN, Mplus, LISREL, PROC MIXED (SAS), and gllamm (Stata) for estimating MLM using data collected with a complex sampling plan. We illustrate how sampling weights need to be constructed for estimating MLM with these software packages. Finally, we contrast the results from these packages using data collected with a complex sampling plan.
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- The address information is for the authors that have a + after their name.
- Authors who are presenting talks have a * after their name.
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