Tag Archives: Multilevel Modeling

IRWS Course Registration

The IRWS 2010 is almost fully booked. Only the following course combination are available:

  • Data Analysis with R
  • Introduction to the SOEP/Analysing Panel Data OR Qualitative Comparative Analysis
  • Network Analysis OR Teching Skills

Please contact the workshop organizers at irws@hsu-hh.de if you want to participate in the workshop.

The courses at the IRWS have at the moment the following number of participants:

Morning Lectures

  • Data Analysis with Stata (Beginners): 21 (fully booked)
  • Data Analysis with R: 16
  • Qualitative (Expert) Interview/MaxQDA: 23 (fully booked)
  • Questionnaire Design: 23 (fully booked)

Afternoon Lectures

  • Introduction to the SOEP/Analysing Panel Data: 27
  • Data Analysis with Stata (Intermediates): 21 (fully booked)
  • Case Study Research/MaxQDA: 25 (fully booked)
  • Qualitative Comparative Analysis: 11

Alsion Lectures

  • Network Analysis: 18
  • Multilevel Modeling: 26 (fully booked)
  • Teching Skills: 16
  • SEM with AMOS: 24 (fully booked)

(last updated: 02.08.2010)

Multilevel Modeling

Institution: see Organisers & Acknowledgements

Program of study: International Research Workshop

Lecturer: Roel de Jong (University of Hamburg)

Date: 06.10.2010, 09:00 – 17:30

Room: n.s.

Max. number of participants: 25

Semester periods per week: n.s.

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English/German (depending on participants)

Contents:
Many research designs in the social, medical and biological sciences yield data that have a hierarchical, nested or clustered structure. Examples include pupils within classes, children within families, occasions within an individual, experiments within batches, tests within laboratories, and so on. Classic statistical techniques fail to take into account that observations from the same cluster are likely to be dependent on each other, and are therefore not suited to analyze such data. Multilevel models have been developed over the last 20 years as an alternative, and are now the de-facto standard for the analysis of data with these complex patterns of variability.

In this course, you will learn :

  • About the structure of multilevel models.
  • How to ascertain the degree to which the observations of the sample are dependent.
  • How to specify and fit multilevel models using statistical software.
  • How to perform statistical tests relevant to the hypotheses at hand.

You have to register for the 4th International Research Workshop to participate in this course.