Course instructions with schedule, VT 2020 (69 Kb) . (PDF)

Time: The course will start with an introduction on January 21 and ends on May 12, 2020. See schedule in the course instructions.

Place: Conference room 357, Frescati Hagväg 14.

Language: English or Swedish

Course Leaders and Examiners: Claudia Bernhard-Oettel and Magnus Sverke

Eligibility Requirement: Accepted for studies at doctoral level in psychology or other social sciences discipline.

Registration: Please send an e-mail to the course administrators at expeditionen@psychology.su.se no later than January 7, 2020.

Application for Graduate Course / Anmälan till kurs på Forskarutbildningen (137 Kb)  (PDF)

Course Description

The objective of this course is to provide the student with a general understanding of Structural Equation Modeling (SEM) and how it can be used. One of the main focuses of the course is on the acquiring of fundamental theoretical knowledge. There will also be an emphasis on having course participants gain first-hand experience using the Mplus software in order to be able to analyze data on their own using SEM. Practical skills are to be acquired through demonstrations and workshops on SEM basics and hands-on exercises, during several class meetings as well as through laboratory group assignments. Regardless of the fact that the course treats SEM from a user perspective (without any pretensions to deeper statistical or theoretical investigation), the careful reading and understanding of rather complicated literature will nevertheless be expected.

The course includes the following aspects of SEM: confirmatory factor analysis, path analysis with latent variables, multi-group analysis, latent class analysis (LCA) and latent profile analysis (LPA), and growth curve modeling (including latent class growth analysis [LCGA]). There are many programs on the market today, but in this course we will be working only with the Mplus program.

Software requirements

Participants are required to bring a laptop with the Mplus program installed to all workshops. Please note that the free Demo version is too limited for the analyses to be conducted during the course. The software (Mplus Version 8 Base Program and the Combination Add-On Single-User License with pdf User's Guide) can be purchased here (note that student pricing is for an individual license bought personally by a student): www.statmodel.com

Expected Learning Outcomes

Upon course completion, the student is expected to be able to:

  • Critically discuss what SEM is and how it can be used
  • Critically analyze in what situations and under what circumstances different types of SEM analysis may be useful
  • Show evidence of good knowledge of the basic assumptions of SEM, estimation methods, and goodness-of-fit indicators
  • Perform common types of SEM analyses using Mplus, and present and interpret results
  • Critically analyze research findings based on SEM.

Examination

Participation in workshops on various SEM applications is mandatory. The examination is based on both group and individual assignments.

Group assignments: The group work will consist of laboratory assignments (in groups of approximately two people), that correspond with the topics of the various seminars. Analyses are to be based on practice data that will be provided during the course. Laboratory assignments are to be submitted in writing before the following seminar (see schedule) and consist of a selection of syntax files, reports on the results of the group’s analyses, and interpretations of these based on course literature.

Individual assignments: There are two types of individual assignments. One of these is a take-home examination where participants are expected to answer, and reflect upon, conceptual issues regarding SEM. The other consists of choosing an empirical article based on SEM, to discuss the analysis in writing, and to briefly present this analysis to the group.

Grading and grade criteria

The grading in the course is on a pass or fail basis, based on the expected learning outcomes. For a passing grade, the doctoral student has participated in the mandatory workshops (or, in the case of absence, provided compensatory tasks), passed the mandatory group assignments, and passed the mandatory individual assignments, whereas the fail grade means that one or several of these requirements have not been met.

Literature

See course instructions. The total amount of literature corresponds to approximately 800 pages plus a software manual.