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

About

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.

Fee info