Spring 2019 Classes in Methodology
If you have a question about a specific course, please contact the instructor of that course directly. If you have a general question about the suite of one-credit methodology courses, please email firstname.lastname@example.org.
For more information about the one-credit courses, please see our frequently asked questions:
BBH 597 Section 002 - Time Varying Effect Models (TVEM)
Instructor: Ashley Linden-Carmichael, Assistant Research Professor of Biobehavioral Health
Time and Location: March 11 - April 15, 2019; 2:30-3:45, 008 Huck Life Sciences Building
Course Description: The goal of this short course is to help you gain the background and skills to be able to identify and address new research questions using time-varying effect modeling (TVEM), a novel method for examining associations across time. Course topics will include discussion of the types of questions that can be addressed using TVEM, models for continuous and binary outcomes, moderation, and weighted analyses. Examples will focus primarily on age-varying effects to study epidemiological and developmental questions in cross-sectional and longitudinal panel data, but will also include applications to intensive longitudinal data.
Prerequisites: Prerequisites are three semesters of graduate-level statistics for the social and behavioral sciences, or three semesters of graduate-level statistics and a demonstrated interest in the social and behavioral sciences. Basic familiarity with SAS is helpful, but not a prerequisite.
HDFS 597 Section 005 - Survey Methodology: Applications for Data Collection and Secondary Data Analysis
Instructor: Cara Rice, Research Associate, The Methodology Center
Time and Location: January 9 - February 15, 2019; 11:15-2:15
Course Description: This course covers the fundamentals of survey methodology with an emphasis on statistical aspects and practical skills necessary for the design of primary sample surveys and for analysis of secondary data sets. Major topics will include various sampling designs (e.g. simple random sampling, stratified random sampling), survey weights, nonresponse mechanisms, and biases that arise in survey research. Application to real data from public health and social/behavioral research will be used to illustrate the material.
Prerequisites: Prerequisites are three semesters of graduate-level statistics for the social and behavioral sciences. Basic familiarity with SAS is also helpful.