MTS 525-0
 Special Topics Research Seminar

Section 20: Generalizing about Message Effects
 Spring 2020

2:00-4:50 p.m. Mondays

via remote instruction



Instructor:       Daniel O’Keefe




Course description: One recurring concern in communication research is understanding how and why messages have the effects they do. This course takes up issues concerning evidence-based generalizations about message effects. It addresses the design and analysis of primary research (e.g., case-category confounds, effect sizes and confidence intervals, the “replication crisis”) and the pursuit of research synthesis through meta-analysis.


Prerequisite: Completion of, or concurrent enrollment in the last term of, a year-long statistics course.


General plan of the course: Class meetings will be devoted to discussion of assigned articles (available online). Students will be expected to participate in discussion and submit a paper on some appropriate topic.


Tentative list of topics: 


TOPIC 1: Primary research design in message effects research

            1.1 The logic of experimental message effects research

            1.2 Single-message designs, case-category confounds

            1.3 Message variation definition

            1.4 Alternative comparison conditions


TOPIC 2: Describing primary research results: NHST and its discontents

            2.1 Null hypothesis significance testing

            2.2 Effect sizes and confidence intervals

            2.3 Message-effect effect sizes


TOPIC 3: The “replication crisis” and affiliated ideas

            3.1 Crises of replication in psychology and other fields

            3.2 Statistical power

            3.3 Questionable research practices


TOPIC 4: Research synthesis via meta-analysis

            4.1 The general idea

            4.2 Formulating the research questions

            4.3 Locating relevant research

            4.4 Managing the information

            4.5 Analytic procedures

            4.6 Reporting meta-analyses


TOPIC 5: Message design guidance: generalization and its alternatives


Home page for this 525 section
Daniel J. O'Keefe home page