Please join instructor Brady T. West of the University Of Michigan's Program in Survey Methodology, as he conducts a half-day workshop titled "Design-Based Analysis of Survey Data". This workshop is designed for survey data analysts of all skill levels, and will present theoretically appropriate methods of analyzing survey data collected from complex sample designs. Dr. West will also present the implications of incorrect analyses based on his research findings from a meta-analysis of analytic error, while also providing examples of proper design-based data analysis techniques using SAS and Stata. As always, this workshop is free and open to the public.
Topics include:
• Overview of theoretically appropriate design-based analysis of survey data collected from complex samples
• Case studies in analytic error (including findings from a meta-analysis of recent scientific publications), and the implications of using incorrect analysis methods
• Appropriate use of survey weights and design-based methods of variance estimation for population inference related to descriptive parameters and regression models
• Examples of proper design-based data analysis techniques using SAS and Stata (attendees are also welcome to ask about similar methods in other software packages)
BIO:
Dr. West's current research interests include the implications of measurement error in auxiliary variables and survey paradata for survey estimation, survey nonresponse, interviewer variance, and multilevel regression models for clustered and longitudinal data. He is the lead author of the book Linear Mixed Models: A Practical Guide Using Statistical Software and co-author of the book Applied Survey Data Analysis.
Topics include:
• Overview of theoretically appropriate design-based analysis of survey data collected from complex samples
• Case studies in analytic error (including findings from a meta-analysis of recent scientific publications), and the implications of using incorrect analysis methods
• Appropriate use of survey weights and design-based methods of variance estimation for population inference related to descriptive parameters and regression models
• Examples of proper design-based data analysis techniques using SAS and Stata (attendees are also welcome to ask about similar methods in other software packages)
BIO:
Dr. West's current research interests include the implications of measurement error in auxiliary variables and survey paradata for survey estimation, survey nonresponse, interviewer variance, and multilevel regression models for clustered and longitudinal data. He is the lead author of the book Linear Mixed Models: A Practical Guide Using Statistical Software and co-author of the book Applied Survey Data Analysis.
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