Due to the Corona Virus the information regarding study and examination for semester 2 (block 3 and 4) is not up-to-date. For the latest news please check the course page in Blackboard/Brightspace.

# Multilevel and Longitudinal Data Analysis

Course
2014-2015

Master’s students in Psychology with a:

• Basic understanding of the concepts underlying multiple regression analysis

## Description

In empirical research we often have nested data. Examples of nested data are when we have measurements of children from different classes or school, and measurements of employees in firms. One important class of nested data is longitudinal data, where there are measurements at different time points nested within an individual.

Nested data create dependent observations, i.e. children in one class are more alike than children from different classes or measurements of one subject are more alike than measurements of different subjects. The statistical analysis needs to take into account this dependency. Two classes of regression models exist that deal with this dependency: the first class ignores the dependency when etsimating the regression weights but adjusts standard errors to obtain valid inference; the second class include includes specific parameters in the regression model that account for the dependency. The latter model is the so-called multilevel regression model.
In this course these two types of regression models will be introduced and explained in much detail.

## Course objectives

The Student

• Learns to distinguish between nested and non-nested data

• Learns the intraclass correlation

• Understands the bootstrap and knows how to use it in longitudinal data analysis

• Learns R software for applying the bootstrap method in longitudinal data analysis

• Acquires a basic understanding of the multilevel model

• Understands how multilevel models deal with dependency

• Learns R software for fitting multilevel models

## Timetable

Multilevel Analysis (2014-2015):

## Registration

### Course

Students need to enroll for lectures and work group sessions. Please consult the Instructions registration

## Mode of instruction

• Seven lectures

• Supervised computer practicals.

## Assessment method

Two take home assignments.

The Faculty of Social Sciences has instituted that instructors use a software programme for the systematic detection of plagiarism in students’ written work. In case of fraud disciplinary actions will be taken. Please see the information concerning fraud

## Blackboard

Multilevel Analysis occasionally uses of the learning environment Blackboard . (http://blackboard.leidenuniv.nl/)