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Foundations of Meta-Analysis
 

Five-day Course • June 8 –12, 2009• Lawrence, Kansas

Sponsored by the Quantitative Psychology Training Program of the Department of Psychology at the
University of Kansas

Objectives

The Institute on Foundations of Meta-Analysis will enable participants to:

  • Understand and critically evaluate published meta-analyses.
  • Develop the skills necessary to conduct and write publishable meta-analytic reviews.
  • Identify the foundations upon which more advanced meta-analytic techniques are based.

Audience

If you are interested in systematically reviewing existing empirical literature and have a basic statistical background, this course is for you. You should have a good working knowledge of the principles and practice of elementary statistics (e.g., t-tests, ANOVA, correlation/regression). No further quantitative training is assumed, although participants with more extensive backgrounds will also benefit from this course.

Participants from a variety of fields, including psychology, education, human development, sociology, marketing, business, biology, medicine, political science, and communication, will benefit from the course.

Instructor

Noel A. Card, Ph.D., is an assistant professor in Family Studies and Human Development at the University of Arizona. He holds a Ph.D. in clinical psychology from St. John's University and completed a postdoctoral fellowship in quantitative and developmental psychology at the University of Kansas. Noel has published and consulted on several meta-analytic reviews and is currently preparing a book, Meta-Analysis: Quantitative Synthesis of Social Science Research. He has received many accolades for his skills at teaching and consulting on advanced quantitative topics.

Software and Other Material

Attendees are encouraged to bring a laptop computer that contains basic spreadsheet (e.g., Excel) and statistical analysis (e.g., SPSS) software. The course will not rely on any specific software packages, but participants who wish to practice techniques will benefit from having these basic capabilities on their computers.

Participants should bring several (e.g., 8–12) articles that they would consider including in a meta-analysis.

Syllabus

Summer Institute on Meta-Analysis

June 8-12, 2009 • Lawrence, Kansas

Noel Card • Assistant Professor, University of Arizona

Monday
9:00–9:45 Welcome and course overview
9:45-10:30 Introduction to meta-analysis
10:45–12:00 Advantages and criticisms of meta-analysis
12:00–1:30 Lunch (provided)
1:30–3:00 Problem formulation and searching the literature
3:15–5:00 Identifying and coding variables in primary literature
6:00 Dinner at Little/Hawley home (provided)
Tuesday
9:00–10:30 Computing effect sizes I: Introduction to effect sizes; computing Z or r from reported data
10:45–12:15 Computing effect sizes II: Computing d or o from reported data; standard errors
12:15–1:30 Lunch (on own)
1:30–3:00 Computing effect sizes III: Correcting effect sizes for artifacts
3:15–5:00 Q&A on searching and study coding / consulting on individual projects
Wednesday
9:00–10:30 Combining effect sizes I: Computing (fixed-effects) mean effect sizes
10:45–11:30 Combining effect sizes II: Evaluating heterogeneity of effect sizes
11:30–1:00 Lunch (provided)
1:00–3:00 Combining effect sizes III: Fixed- and random-effects models
3:15–5:00 Q&A on combining effect sizes / consulting on individual projects
Thursday
9:00–10:30 Comparing effect sizes I: Categorical moderator analysis
10:45–12:00 Comparing effect sizes II: Continuous moderator analysis
12:00–1:30 Lunch (on own)
1:30–3:00 Comparing effect sizes III: Multiple / confounded moderators
3:15–5:00 Q&A on moderator analyses / consulting on individual projects
Friday
9:00–10:30 Diagnostics (e.g., evaluating publication bias)
10:45–12:00 Reporting results of a meta-analysis (graphical displays; writing tips)
12:00–1:00 Lunch (provided)
1:00–4:00 Wrap-up / consulting on individual projects


Detailed Syllabus Here

Contact Information

For information on course content, contact Noel A. Card: ncard@email.arizona.edu.

For information on registering, contact Todd D. Little: yhat@ku.edu.


Please send questions or comments concerning this Web site to Devin Sinha .