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Activity Number:
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564
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Type:
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Contributed
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Date/Time:
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Wednesday, August 3, 2016 : 11:35 AM to 12:20 PM
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Sponsor:
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Survey Research Methods Section
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Abstract #321736
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Title:
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A Comparison Between Standard Regression and Multilevel Modeling Techniques to Analyze Complex Survey Data Based on the Monte Carlo Simulation Study
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Author(s):
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Alomgir Hossain* and George Wells and Punam Pahwa
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Companies:
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University of Ottawa Heart Institute and University of Ottawa Heart Institute and University of Saskatchewan
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Keywords:
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Multistage ;
complex survey ;
scaled-weight
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Abstract:
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Complex surveys based on multistage design are commonly used to collect large population data. Stratification, clustering and unequal probability of the selection of individuals are the complexities of complex survey design. Statistical techniques such as the multilevel modeling- scaled weights technique and the standard regression - robust variance estimation technique are used to analyze the complex survey data. Both statistical techniques take into account the complexities of complex survey data but the ways are different. Performance of these two techniques will be examined by Monte Carlo simulation based on Canadian Heart Health Survey (CHHS) or Statistics Canada 2012-Canadian Community Health Survey.
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Authors who are presenting talks have a * after their name.
