Winter School in Empirical Research Methods
MEDIATION, MODERATION, AND CONDITIONAL PROCESS ANALYSIS
PREREQUISITES (KNOWLEDGE OF TOPIC)
Participants should have a basic working knowledge of the principles and practice of multiple regression and elementary statistical inference. No knowledge of matrix algebra is required or assumed, nor is matrix algebra ever used in the course.
Participants are strongly encouraged to bring their own laptops (Mac or Windows)
Computer applications will focus on the use of OLS regression and the PROCESS macro for SPSS and SAS developed by Andrew F. Hayes (processmacro.org) that makes the analyses described in this class much easier than they otherwise would be. Because this is a hands-on course, participants are strongly encouraged to bring their own laptops (Mac or Windows) with a recent version of SPSS Statistics (version 19 or later) or SAS (release 9.2 or later) installed. SPSS users should ensure their installed copy is patched to its latest release. SAS users should ensure that the IML product is part of the installation. R and STATA users can benefit from the course content, but PROCESS makes these analyses much easier and is not available for R or STATA.
Statistical mediation and moderation analyses are among the most widely used data analysis techniques in social science, health, and business fields. Mediation analysis is used to test hypotheses about various intervening mechanisms by which causal effects operate. Moderation analysis is used to examine and explore questions about the contingencies or conditions of an effect, also called “interaction”. Increasingly, moderation and mediation are being integrated analytically in the form of what has become known as “conditional process analysis,” used when the goal is to understand the contingencies or conditions under which mechanisms operate. An understanding of the fundamentals of mediation and moderation analysis is in the job description of almost any empirical scholar. In this course, you will learn about the underlying principles and the practical applications of these methods using ordinary least squares (OLS) regression analysis and the PROCESS macro for SPSS and SAS.
60% of assessment will be based daily homework assignments and 40% will be based on a written final examination at the end of the course. The exam and homework will be a combination of multiple choice questions and short-answer/fill in the blank questions, along with some interpretation of computer output. Homework questions will be posted at the end of class on Monday – Thursday and turned in the following day. Students will take the final exam home on the last day of class and return it to the instructor within one week.
For homework and during the examination students will be allowed to use all course materials, such as PDFs of PowerPoint slides, student notes taken during class, and any other materials distributed or student-generated during class. Although the book mentioned in “Literature” is not a requirement of the course nor is it necessary to complete the assignments, students may use the book if desired.
A computer is not required to complete the assignments, though students may use a computer if desired, for example as a storage and display device for class notes provided to them during class.
The topics of the homework and exam may include how to quantify and interpret path analysis models, calculate direct, indirect, and total effects, and determine whether evidence of a mediation effect exists in a data set based on computer output provided or other information. Also covered will be the testing moderation of an effect, interpreting evidence of interaction, and probing interactions. Students will be asked to generate or interpret conditional indirect effects from computer output given to them and/or determine whether an indirect effect is moderated. Students may be asked to construct computer commands that will conduct certain analyses. All questions will come from the content listed in “Course Content” above.
For more information click "LINK TO ORIGINAL" below.