Applied Statistics for Educational Researchers (DUH165)

This course is organized in several workshops in one week and will provide an introduction to structural equations models (SEM), latent interactions, multilevel SEM, and latent growth curve modeling. We will use the software package Mplus, and the software R will be introduced towards the end of the course.


Course description for study year 2024-2025

Facts

Course code

DUH165

Version

1

Credits (ECTS)

5

Semester tution start

Spring

Number of semesters

1

Exam semester

Spring

Language of instruction

English

Offered by
Time table

View course schedule

Content

This seminar is organized in several workshops and will introduce in structural equations models (SEM) with interactions, multilevel SEM and growth curve modeling. We will use the software package Mplus, and R will be introduced.

Learning outcome

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

Knowledge:

    • of measurement theory
    • a good understanding of multiple regression and factor analysis in SEM
    • a good understanding of hierarchical structures in data, and how to address them in analysis a good
    • a good understanding of SEM and LGC in complex survey data

Skills:

    • running SEM and LGC analyses in Mplus
    • preparing results of such analyses for publication

General competencies:

    • being able to choose and apply the right analyses for the given design and data
    • developing advanced strategies for further research

Required prerequisite knowledge

None

Recommended prerequisites

The students are expected to have the software package Mplus ready and installed on their personal computers, to know the data structure of their projects and the research questions and get themselves acquainted with Mplus, and to some extent in R prior to the course so that they master to prepare the data for import in Mplus, know some basic Mplus syntax (chapters 1 + 2 in Muthén & Muthén), and to have some datasets prepared in the right format (.dat or .csv) for Mplus and/ or R.

Exam

Form of assessment Weight Duration Marks Aid
Paper 1/1 Passed / Not Passed

Evaluation will be based on active participation and analyses performed in an individual paper (Max. 4000 words). Coursework requirements: Active participation in lectures and seminars at the workshop. Self-study. The student’s workload will be approximately 150 hours of work

Coursework requirements

80 % attendance
At least 80 % attendance in lectures and seminares.

Course teacher(s)

Course teacher:

Simona Carla Silvia Caravita

Course teacher:

Njål Foldnes

Course teacher:

Thormod Idsøe

Course coordinator:

Lene Vestad

Study Program Director:

Hein Berdinesen

Course teacher:

Ulrich Dettweiler

Course teacher:

Knud Knudsen

Method of work

In the seminar, we will introduce CFA and SEM and see how latent interaction effects and multilevel modeling work in the SEM framework. Moreover, the course demonstrates how Latent Growth Curve modeling (LGCM) can be understood as an extension of SEM with intercepts and/or slopes being modeled as latent variables, first as an unconditional latent curve model. We will then look at conditional LGCM. The analyses will be demonstrated primarily in Mplus. The LGCM will also be replicated and shown together with an introduction to R.

The working format blends lectures, group discussions, and hands-on analyses in Mplus/ and in R.

Overlapping courses

Course Reduction (SP)
Advanced Statistics for Educational Researchers: Analyzing Structural Equation Models and Latent Growth Curves w/ MPlus (DSP165_1) 5

Open for

International and local students enrolled in a doctoral program. Max. 25 participants.

Course assessment

There must be an early dialogue between the course supervisor, the student union representative and the students. The purpose is feedback from the students for changes and adjustments in the course for the current semester.In addition, a digital subject evaluation must be carried out at least every three years. Its purpose is to gather the students experiences with the course.

Literature

Search for literature in Leganto