By completion of this course, the PhD candidate will have gained the following:
of measurement theorya good understanding of multiple regression and factor analysisa good understanding of hierarchical structures in data, and how to address them in analysisa good understanding of SEM and LGC in complex survey datanewline
running SEM and LGC analyses in MPluspreparing results of such analyses for publicationnewline
being able to choose and apply the right analyses for the given datadeveloping advanced strategies for further research
This PhD course will introduce educational researchers to SEM and LGC and enable the successful candidate to apply those analyses in her own research using the software package MPlus.
The course will be held over three workshops with practice time in between. We encourage participants to bring own data for analysis so that we can work in groups on “real” projects.
Know your project and the research questions thoroughly. Get yourself acquainted with MPlus prior to the course so that you feel competent to prepare the data for import in Mplus, and know some basic syntax (chapters 1 + 2 in Muthén & Muthén). Have some datasets prepared in the right format (.dat) for MPlus.
Eksamen / vurdering
Pass - Fail
Evaluation will be based on the active participation and analyses performed in group work, presented in a brief paper. Coursework requirements: Active participation in lectures and seminars at the workshop. Self-study. The students’ workload will be approximately 150 hours of work.
80 % attendance
At least 75 % attendance in lectures and seminares.
The next step is to look at more complex applications of SEM, i.e. mediation models, hierarchical /multilevel models, and comparison of (latent) groups with different approaches of testing measurement invariance. Tutors: Lars-Erik Malmberg (Oxford), Ulrich Dettweiler (UiS)
International and local students enrolled in a doctoral program. Max. 25 participants. WNGER II students will be prioritized up to a quote of 10.
A dialogue with the students to gain information for similar courses in the future. Final discussion with the students and concluding report from the course leader. The course will be included in the evaluation procedure of the PhD programs at the faculty.
Applied Statistics for Educational Researchers (DUH165)
Literature (ca. 500 pages):
Selected chapters of:
Bollen, K. A. (2006). Latent curve models: a structural equation perspective. Hoboken, N.J: Wiley-Interscience.
Kline, R. B. (2011). Principles and practice of structural equation modeling (3. ed.). New York: Guilford Press.
Muthén, L.K. and Muthén, B.O. (1998-2017). Mplus User’s Guide. Eighth Edition. Los Angeles, CA: Muthén & Muthén