MET522A Multivariate Data Analysis

• Topics

  The course gives the participants an understanding of structural equation modeling (SEM) by relating it to the participants’ previous knowledge of multiple linear regression, and then by expanding it to allow for correlated and causally related latent constructs.

  The course starts with path analysis among measured variables. Thereafter, the course moves into confirmatory factor models, structural models involving latent causality, and finally into multi-group models and a preview of more advanced topics. Examples from a variety of disciplines will be accompanied.

  The participants will be exposed to different statistical analyses, such as, OLS regression analysis including ANOVA and ANCOVA, logistic - and probit regression, the multivariate linear model, exploratory - and confirmatory factor analysis, measurement models structural equation models, and power analysis.

• Learning outcome

  Upon course completion, the candidate can:

  Knowledge:

  • Apply and understand key classical methods in multivariate statistics, and develop their own statistical "tool box" based on existing knowledge in the field.

  Skills:

  • Use modern statistical software programs and apply these programs on research projects.

  General competence:

  • Understand and interpret statistical analyses and to discuss and raise questions related to the use of different methods in multivariate statistics.

• Teaching

  Lectures and software exercises.

• Restricted access

  • PhD candidates at NHH
  • PhD candidates at Norwegian institutions
  • PhD candidates at other institutions
  • PhD candidates from the ENGAGE.EU alliance
  • Motivated master’s students may be admitted after application, but are subject to the approval from the course responsible on a case by case basis
  • Individuals outside academia may be admitted after application, but are subject to the approval from the course responsible and the Vice Rector for Research on a case by case basis

  There is no cap on the number of students.

  NHH Research Scholars should register for the course as recommended.

• Recommended prerequisites

  OLS Regression

• Required prerequisites

  Basic course in statistics

• Assessment

  Individual term paper.

  Re-take is offered the semester after the course was offered for students who signed up for the initial evaluation.

• Grading Scale

  Karakterskala A-F.

• Literature

  Jöreskog, Olsson, and Wallentin (2016): Multivariate Analysis with LISREL. 1st ed. Springer International Publishing. A PDF will be provided.

  Recommended reading:

  Handouts in multivariate statistics (under preparation)

• This is an ENGAGE-course

  This course is offered to PhD candidates from the ENGAGE.EU alliance.