Levelling up Group

• Levelling Up Statistics
• Basic Economics
• New Social Developments
• Concepts of Social Policy
• Labour Market Policy
• Analytical Demography

Socio Economic Policy Group

• Social Problems and Reforms Seminar
• Social Policy
• Comparative and International Socio-economic Policy

Policy Evaluation Group

• The Policy Cycle
• Evaluation Techniques and Tools

Statistics & Research Group

• Statistics & Research Methods part 1
• Statistics & Research Methods part 2

Master Dissertation

• Master Dissertation

0ptional courses

• Applied Methodology
• Performance audit in social policy

Courses: Statistics & Research Methods - part 2

Teaching Staff

Prof. Jeroen Vermunt (Tilburg University, The Netherlands)
Dr. Guy Moors (Tilburg University, The Netherlands)

Module1: Logistic regression and latent class analysis (Prof. Vermunt)

Objectives

The aim of the course is to gain practical and theoretical knowledge in the most relevant categorical data analysis techniques.

Contents

Odds and odds-ratios, likelihood-ratio chi-squared statistics, logistic regression models for binary, nominal and ordinal response variables, Poisson regression, and latent class modeling

Module 2: growth models and event history analysis (Prof. Moors)

Objectives

How do educational grades change in time? Does a particular educational program affect how school performance changes in time? How long does it take a graduate to find a job? What causes people to marry? What factors influence the decision to look for a new job? What is the likelihood of recidivism in crime and what fosters recidivism? There are plenty of examples in social science research in which researchers are interested in explaining individual changes in time and in estimating the duration and occurrences of events in the life cycle of persons and on the factors that bring about these events. The objective of this part of the course is to develop an understanding of need of particular research methods to analyze individual growth data and event history data.

Contents

Individual growth models:

• why do we need special techniques for analyzing individual changes?
• basic concepts: level-1 submodel for individual change, level-2 submodel for systemactic differences in change between individuals, fitting the multilevel model for change data

Event history analysis:

• why do we need special techniques for analyzing event history data?
• basic concepts in event history analysis: censoring, entry into the risk set, censoring and event time, time varying covariates, discrete time event history analysis of a single non-repeatable event , extensions: multiple events, competing risks, and repeatable events