Short Courses in Social Science Methods - Spring 2014

We would like to bring your attention to two short courses being offered in the spring as part of a social science methods collaborative training program. The goal of this program is to offer 1 and 2-credit short courses in applied methodology intended for faculty and graduate students interested in acquiring new methodological skills to advance their research. This program will be launched in spring 2014 with the following courses:

·         Applied Multilevel Modeling (1 cr), 9am-noon Friday, 4 meetings (4/11, 4/18, 4/25, 5/2)

·         Survey Research Methodology (2 cr), 5-7:30pm Tuesday, meets first 10 weeks only

SOC 682-003 Applied Multilevel Modeling (Brea Perry, Sociology)

This short course will provide an introduction to multilevel modeling (i.e. hierarchical linear modeling, variance components modeling). The course emphasizes conceptual issues and practical application of this versatile method using the statistical software package Stata. Multilevel models are ideal for analyzing clustered data (e.g., persons nested in groups), where predictors are characteristics of individuals or clusters (i.e. groups), or interactions between these. This course will also provide a useful foundation for those interested in longitudinal or growth curve modeling, though we will not focus on the particular issues endemic to longitudinal data analysis. The course will be organized to take participants through each of the cumulative steps in multilevel analysis: deciding which type of model is appropriate, setting up the data file, evaluating fixed and random effects, predicting between- and within-unit variation using covariates, interpreting and displaying empirical findings, and presenting results in both graphic and written form. Participants should be familiar with the general linear model (e.g., ANOVA and regression), but no prior experience with multilevel models or knowledge of advanced mathematics (e.g., matrix algebra) is assumed.

A&S 500-003 Survey Research Methodology (Justin Wedeking, Political Science)

The course is designed to provide an introduction and survey of the literature in survey research methodology as well as provide lab skills in the analysis and handling of survey data. Because the breadth and depth of the field is enormous, where each topic below could likely be expanded to several or more weeks, the course will not attempt to cover everything. Rather, it will take a topical approach, highlighting some of the seminal works in the field and also touching on some recent trends and emerging issues, as well as incorporate computer lab sessions on ways to analyze survey data. Topics include: introductory and history of the field, survey errors and theories of the survey response, measurement issues (e.g., closed vs. open ended, rankings, ratings, branching, scaling, response order), sampling, coverage error, nonresponseerror, data collection (e.g., mode, interviewer effects, etc.), and survey experiments.