Course Description
Meta-analysis in HDFS/related social sciences. This course covers all steps of performing a meta-analysis, including developing research questions, searching for literature, coding effect sizes and study characteristics, analyzing meta-analytic data, and preparing a publishable manuscript. Students will use Excel, SPSS, Mplus, and/or R packages at various steps of meta-analytic review.
Athena Title
Meta-Analysis for FSS
Prerequisite
HDFS 7170 or permission of department
Semester Course Offered
Not offered on a regular basis.
Grading System
A - F (Traditional)
Course Objectives
This course covers the entire process of conducting a meta-analytic review, namely (1) developing research questions appropriate for meta-analysis, (2) searching the literature, (3) coding studies, (4) perform analyses, and (5) writing (or otherwise presenting) the meta-analysis. By the end of this course, students should develop: · The ability to understand and critically evaluate published meta-analyses. · The skills necessary to conduct publishable meta-analytic reviews. · The foundations upon which to learn more advanced meta-analytic techniques and related research synthesis approaches.
Topical Outline
I. Planning a meta-analytic review a. Introduction to meta-analysis b. Questions that can be answered through meta-analysis c. Advantages and criticisms of meta-analysis II. Searching and coding the literature a. Study eligibility criteria b. Searching and retrieving literature c. Introduction to publication bias d. Developing a coding protocol e. Evaluating coding III. Computing effect sizes a. Basic effect size computation b. Correcting for study artifacts c. Coding alternative effect sizes IV. Analyses a. Computing mean effect sizes and heterogeneity b. Random effects models c. Moderator analysis – ANOVA-based approaches d. Moderator analysis – regression-based approaches (AKA meta-regression) e. Mixed-effects models f. Dependent effect sizes g. Meta-Analytic Structural Equation Modeling h. Applications of moderator analysis (e.g., cross-temporal MA, lag as moderator MA, spatiotemporal MA) i. Analyses to detect publication bias V. Related topics: a. Integrative data analysis b. Replication, open science, and meta-analysis VI. Reporting meta-analyses a. Graphical displays b. Writing a meta-analysis manuscript
Syllabus
Public CV