Multi-Level Regression Analysis of Cross-Sectional and Panel Data with R

The course covers multi-level linear regression with R for two types of data; individuals nested within social contexts (e.g. cross-national surveys), and repeated observations from individuals (e.g. longitudinal panel studies).

Course leader

Rob Eisinga
Professor of quantitative research methods
Radboud University Nijmegen

Target group

- Master
- PhD
- Post-doc
- Professional

This PhD level course is open to all researchers aiming at bringing their research to the next level. It is particularly designed for those who conduct cross-context comparative research such as cross-national study and for those involved in the analysis of two or multi-wave panel data.

Course aim

After this course you are able to:

- Recognize nested data structures and know that analysis should account for the nested nature.
- Formulate and fit multilevel linear regression models for the analysis of nested cross-sectional and repeated measures in panel - data.
- Accurately interpret the results of these analyses.
- Analyse multilevel data (and also non-nested data) with the R software.

Credits info

2 EC
2 ECTS credits, with the possibility of an extra 1-3 ECTS credits depending on additional course work and assignments handed in during or after the summer school (for a possible total of up to 5 ECTS).

Fee info

EUR 575: The fee includes the registration fees, course materials, access to library and IT facilities, coffee/tea, lunch, and a number of social activities.

Scholarships

We offer several reduced fees:
€ 518 early bird discount- deadline 1 April 2022 (10%)
€ 489 partner + RU discount (15%)
€ 431 early bird + partner + RU discount (25%)