Analysis of Complex Sample Survey Data

This course provides practical methods and tools to analyze complex survey data with a hands-on introduction to the use of specialized statistical software procedures. The course focuses on case studies with specific large-scale national surveys: the National Comorbidity Survey-Replication (NCS-R), the National Health and Nutrition Examination Surveys (NHANES), and the Health and Retirement Study (HRS). Relevant design features of the NCS-R, NHANES and HRS include survey weights that take into account differences in probability of selection into the sample and differences in response rates, as well as stratification and clustering in the multistage sampling procedures used in identifying the sampled households and individuals. After introducing essential concepts related to complex sample designs, the course will turn to the construction of survey weights, estimation of sampling variance, descriptive analysis, regression analysis, and finally special topics in the analysis of survey data. Participants can expect to work on homework exercises, computer lab exercises, and a final analysis project.

Why take this course? 

  • To gain an understanding of modern methods and software for the secondary analysis of survey data collected from large complex samples
  • To have the opportunity for one-on-one interaction with the instructors when walking through analyses of survey data
  • To see various examples of applied statistical analyses of survey data
  • To have the experience of writing a scientific paper that presents an analysis of complex sample survey data, and getting expert feedback on that paper

Prerequisite: Two graduate-level courses in statistical methods, familiarity with basic sample design concepts, and familiarity with data analytic techniques such as linear and logistic regression.

SurvMeth 614 (3 credit hours)
Instructor: Brady T. West
Textbook Information: Applied Survey Data Analysis-ISBN 9781498761604