Complex sample designs such as stratified cluster sampling make it possible to extract maximum information at minimum cost, but they are typically harder to work with than simple random samples. How do you analyze the resulting data – in particular, how do you determine margins of error? This course teaches you how to estimate variances when analyzing survey data from complex samples, and also how to fit linear and logistic regression models to complex sample survey data.
Dr. Brady T. West
Dr. Brady T. West is a Research Associate Professor in the Survey Research Center at the University of Michigan Institute for Social Research. His current research interests include survey nonresponse, interviewer variance, responsive and adaptive survey design, the analysis of complex sample survey data, and multilevel regression models for clustered and longitudinal data. He teaches several yearly short courses on statistical methodology and software, and is a lead or co-author on numerous publications presenting analyses of complex sample survey data.