Syllabus for Structural Equation Models

Strukturella ekvationsmodeller

Syllabus

  • 7.5 credits
  • Course code: 2ST114
  • Education cycle: Second cycle
  • Main field(s) of study and in-depth level: Statistics A1N

    Explanation of codes

    The code indicates the education cycle and in-depth level of the course in relation to other courses within the same main field of study according to the requirements for general degrees:

    First cycle

    • G1N: has only upper-secondary level entry requirements
    • G1F: has less than 60 credits in first-cycle course/s as entry requirements
    • G1E: contains specially designed degree project for Higher Education Diploma
    • G2F: has at least 60 credits in first-cycle course/s as entry requirements
    • G2E: has at least 60 credits in first-cycle course/s as entry requirements, contains degree project for Bachelor of Arts/Bachelor of Science
    • GXX: in-depth level of the course cannot be classified

    Second cycle

    • A1N: has only first-cycle course/s as entry requirements
    • A1F: has second-cycle course/s as entry requirements
    • A1E: contains degree project for Master of Arts/Master of Science (60 credits)
    • A2E: contains degree project for Master of Arts/Master of Science (120 credits)
    • AXX: in-depth level of the course cannot be classified

  • Grading system: Fail (U), Pass (G), Pass with distinction (VG)
  • Established: 2011-02-04
  • Established by:
  • Revised: 2022-10-14
  • Revised by: The Department Board
  • Applies from: Autumn 2023
  • Entry requirements:

    120 credits including 90 credits in statistics, or 120 credits including 60 credits in statistics and 30 credits in mathematics and/or computer science.

  • Responsible department: Department of Statistics

Learning outcomes

A student who has gone the course should

- have a basic theoretical and practical understanding of Structural Equation Models (SEM)

- be able to apply SEM on real problems

- have ability to interpret and present the results.

- be able to estimate structural equation models with maximum likelihood and least squares and be able to evaluate the results.

Content

The course deals with the logical and the statistical theory of SEM. The practical use of models and methods as a research aid within the social and behavioural disciplines. The course covers modern statistical aspects on regression analysis, exploration and confirmative factor analysis, and general structural equations with and without latent variables for one or more groups.

The course deals with estimation methods for structural equation models based on various types of data: normal distributed ordinal data. Robust estimation methods.

Instruction

Lectures and computer exercises.

Assessment

The examination takes place in the form of a written exam, assignments and presentation of scientific articles.

"If there are special reasons for doing so, an examiner may make an exception from the method of assessment indicated and allow a student to be assessed by another method. An example of special reasons might be a certificate regarding special pedagogical support from the University's disability coordinator."

Syllabus Revisions

Reading list

Reading list

Applies from: Autumn 2023

Some titles may be available electronically through the University library.

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