Hopp til hovedinnhold

Advanced Statistics for Educational Researchers: Analyzing Structural Equation Models and Latent Growth Curves w/ MPlus DSP165

Workshop 1, 1 day: Introducing the software package MPlus, core concepts of multiple regression and factor analysis, preparing for SEM.

 

Workshop 2, 2 days: SEM and LGC as an extension of SEM with intercepts and/or slopes modelled as latent variables.

 

Workshop 3, 2 days: More complex applications of SEM and comparison of (latent) groups with different approaches of testing measurement invariance.


Course description for study year 2020-2021. Please note that changes may occur.

Facts
Emnekode

DSP165

Vekting (SP)

5

Semester undervisningsstart

Spring

Antall semestre

1

Vurderingsemester

Spring

Undervisningsspråk

English

Tilbys av

Faculty of Arts and Education, Department of Cultural Studies and Languages

Learning outcome

By completion of this course, the PhD candidate will have gained the following:

Knowledge

  •  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

Skills:

  •  running SEM and LGC analyses in MPluspreparing results of such analyses for publicationnewline

General competences:

  •  being able to choose and apply the right analyses for the given datadeveloping advanced strategies for further research
Content

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.

 

Course leader:

Ulrich Dettweiler (UiS)

Instructors:

Knud Knudsen (UiS), Thormod Idsøe (NUBU, UiS), Lars-Erik Malmberg (Oxford University)

Required prerequisite knowledge
None
Recommended prerequisites
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
Vurderingsform Vekting Varighet Karakter Hjelpemiddel
Paper 1/1 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.

Coursework requirements
80 % attendance
At least 75 % attendance in lectures and seminares.
Course teacher(s)
Course teacher: Lars-Erik Joakim Malmberg
Course teacher: Thormod Idsøe
Course coordinator: Ulrich Dettweiler
Course teacher: Knud Knudsen
Method of work

Three workshops:

Workshop 1, 1 day, JANUARY 14, 2020:

We will introduce the software package MPlus, resume core concepts of multiple regression and factor analysis, and get ready for SEM.

Tutors: Knud Knudsen (UiS), Ulrich Dettweiler (UiS)

 

Workshop 2, 2 days, FEBRUARY 11-12, 2020:

We will go deeper into SEM and see how LGC can be understood as an extension of SEM with intercepts and/or slopes being modelled as latent variables.

Tutors: Thormod Idsøe (NUBU), Knud Kundsen (UiS), Ulrich Dettweiler (UiS)

 

Workshop 3, 2 days: March 24-25, 2020

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)

 

Open for
International and local students enrolled in a doctoral program. Max. 25 participants. WNGER II students will be prioritized up to a quote of 10.
Course assessment
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.
Overlapping courses
Course Reduction (SP)
Applied Statistics for Educational Researchers (DUH165) 5
Literature

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