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IN PERSON – 5-day Statistics Short Course


Seminar Overview:

This seminar teaches the skills necessary to conduct and write publishable meta-analytic reviews, including methods of searching the empirical literature, coding effect sizes, and analyzing effect sizes across multiple studies.

Seminar Topics:

  • Coming Soon…

Seminar Description:

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Instructor: Noel Card, Ph.D.

Noel is an associate professor Educational Psychology at the University of Connecticut. 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 received many accolades for his skills at teaching and consulting on SEM issues and concepts, and has worked extensively in applying SEM to longitudinal and dyadic data. Noel Card’s research interests are in developmental science and quantitative methods, and especially at the interface of these disciplines. His developmental interests are broadly within the domain of child and adolescent social development, with specific interest in aggression and peer victimization. His quantitative interests are primarily in meta-analysis, with additional interests in structural equation modeling, analysis of longitudinal data, and analysis of interdependent data.

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APA Continuing Education Credits:

This course offers 24 hours of Continuing Education Credits. Stats Camp Foundation is approved by the American Psychological Association to sponsor continuing education for psychologists. Stats Camp Foundation maintains responsibility for this program and its content.

Seminar Includes:

Materials, downloads, recorded course video viewable for up to one year.

Learning Objectives:

After engaging in course lectures and discussions as well as completing the hands-on practice activities with real data, participants will be able to:

  • Describe the kinds of questions that can be answered using meta-analysis.
  • Search the literature guided by a meta-analysis framework.
  • Code study characteristics valuable to meta-analysis.
  • Compute effect sizes.
  • Correct effect sizes for artifacts of the study.
  • Code alternative effect sizes.
  • Compute mean effect sizes and heterogeneity.
  • Conduct random effects models in a meta-analysis framework.
  • Conduct a moderator analysis in a meta-analysis framework, including mixed-effects models.
  • Account for publication bias when conducting a meta-analysis.
  • Understand key steps in an integrative data analysis.
  • Report the findings of a meta-analysis.

Seminar Prerequisites:

Coming Soon…

Software and Computer Support:

Dr. Card does not use any specialized software for this meta-analysis seminar.

Seminar Audience:

If you are interested in systematically reviewing existing empirical literature and have a basic statistical background, this seminar 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 seminar.

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

Seminar Files

Below are links to seminar files for those who enrolled in the seminar. Please download these files onto your computer before the first day of the seminar. The files are password protected to respect the intellectual property rights of the instructors. By using your login information you agree not to share your login information or the content protected by it.

Instructor will provide password on first day of seminar:
Click Here to Access Meta- Analysis Seminar Files

All statistical software used at Stats Camp will be available, free to participants, on our SMORS (statistical modeling on remote servers) system for the duration of camp.

Summer Stats Camp 2023: Meta-Analysis
Monday June 5, 2023
9:00 – 9:30 Welcome and course overview (Lecture 00)
9:30 – 10:45 Introduction to meta-analysis (Lecture 01)
10:45 – 11:00 Rest Break
11:00 -12:30 Questions that can be answered through meta-analysis (Lecture 02)
12:30 – 1:30 Rest Break
1:30 – 3:15 Searching the literature (Lecture 03)
3:15 – 3:30 Rest Break
3:30 – 5:00 Coding study characteristics (Lecture 04)
Tuesday June 6, 2023
9:00 – 10:45 Basic-effect size computation (Lecture 05)
10:45 – 11:00 Rest Break
11:00 -12:30  Lecture 5 continued; Correcting effect sizes for artifacts (Lecture 06)
12:30 – 1:30 Rest Break
1:30 – 3:15 Coding alternative effect sizes (Lecture 07)
3:15 – 3:30 Rest Break
3:30 – 5:00 Individual / small group consulting and Q&A
Wednesday June 7, 2023
9:00 – 10:45 Computing mean effect sizes and heterogeneity (Lecture 08)
10:45 – 11:00 Rest Break
11:00 -12:30 Random effects models (Lecture 09)
12:30 – 1:30 Rest Break
1:30 – 3:15 Moderator analysis (Lecture 10)
3:15 – 3:30 Rest Break
3:30 – 5:00 Individual / small group consulting and Q&A
Thursday June 8, 2023
9:00 – 10:45 Moderator Analysis (continued); Mixed-effects models (Lecture 11)
10:45 – 11:00 Rest Break
11:00 -12:30 Applications of moderator analysis (Lecture 12)
12:30 – 1:30 Rest Break
1:30 – 3:15 Publication bias (Lecture 13)
3:15 – 3:30 Rest Break
3:30 – 5:00 Individual / small group consulting and Q&A
Friday June 9, 2023
9:00 – 10:45 Integrative data analysis (Lecture 14); Replication (Lecture 15)
10:45 – 11:00 Rest Break
11:00 -12:30 Replication (continued); Reporting meta-analyses (Lecture 16)
12:30 – 1:30 Rest Break
1:30 – 4:30 Individual / small group consulting and Q&A

Please fill out and submit the form below to get instant access to sample course materials.

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