Students (2) Seminar Grand Total $1,095 that’s $795 off your second course use code. ALLWEEKSTUDENT
Faculty (2) Seminar Grand Total $1,795 that’s $595 off your second course use code. ALLWEEKFACULTY

Multilevel Modeling for Grouped & Longitudinal Data

Session 1: May 1 – 3, 2017
Lisbon, Portugal
DoubleTree by Hilton Lisbon – Fontana Park

Payment Options
Per Course Qty
Facultyshow details + $1,195.00 (USD)  
Studentshow details + $945.00 (USD)  

Statistics Seminar Objectives

This 2.5 day training institute on Multilevel Modeling for Grouped and Longitudinal Data introduces the use of multilevel models (a.k.a. mixed models, hierarchical linear models) for the analysis of grouped and longitudinal data. Course objectives are:

  • Deciding on the appropriate model
  • Managing the data
  • Assessing fixed and random effects
  • Evaluate alternative covariance structures for longitudinal data
  • Estimating multilevel generalized models.

Seminar Syllabus

The following schedule is tentative. Because of the short duration of the course, and depending on the needs of the participants some topics may start a little earlier, or run a little longer than shown below.

Monday, May 1 9:00-5:00

  • Introduction to multilevel analysis. When should it be used, and why? Introduction of the basic two- and three-level regression model. Discussion of the logic of the two-level regression model, using a simple example. Choice of estimation method
  • Analyzing longitudinal data. The difference between fixed and varying occasions. Time invariant and time varying covariates. Advantages of multilevel analysis of longitudinal data. The problem of autocorrelation.

Lunch Break 12:30 – 1:30

  • Introduction to the HLM computer program. How to enter data. Discussion of example data set. Brief discussion of other software.
  • Computer lab: multilevel regression exercises in HLM.
  • Reading: Multilevel Analysis: chapter 2+5.

Tuesday, May 2 9:00-5:00

  • The problem of non-normal data: dichotomous data and proportions. Introduction to the generalized linear model, and its multilevel extension. Discussion of some available choices of estimation procedure.
  • Generalized linear model for ordinal and count data.

Lunch Break 12:30 – 1:30

  • Example of using HLM on data that consists of proportions and ordinal data.
  • Computer lab: modeling non-normal data.
  • Reading: Multilevel Analysis: chapter 6 & 7.

Wednesday, May 3 9:00-12:30

  • Analysis strategy
  • Explained variance
  • Standardizing regression coefficients
  • Assumptions and robust estimation
  • Reading: Multilevel Analysis: chapter 13.


Why Should You Attend?

  • Get 1 on 1 Consultation With Instructor
  • Professional Networking
  • Peer Socializing
  • Collaboration
  • All Course Resources
  • Breakfast (For Students Staying At Venue Hotel)
  • Lunch, and All-Day Tea/Coffee/Snack Service
  • After Class Networking Mixers

Statistical Methods Seminar Description


The purpose of this course is to help researchers and students who want to apply multilevel techniques in their research. The course considers multilevel regression models in detail.

It starts with an introduction to the basic two- and three-level regression model, estimation methods, and interpretation of results. Next, it discusses longitudinal models, and models for non-normal data such as multilevel logistic regression models. Although this is not a computer course, references are made to multilevel software packages, and there are software demonstrations on example data sets. The general structure of the course is a lecture in the morning and a computer lab in the afternoon for the first two days. The third day treats a variety of statistical issues, such as explained variance, standardizing coefficients, assumptions and robust estimation.

Instructor: Joop Hox

Hox attended the Bisschoppelijk College Roermond from 1962 to 1968, and the Whitman College from 1968 to 1969. After receiving his MS in psychology, he received his PhD in 1986 from the University of Amsterdam under supervision of Don Mellenbergh with a thesis, entitled “Het gebruik van hulptheorieën bij operationalisering: een studie rond het begrip subjectief welbevinden” (The use of auxiliary theories on operationalization: a study of the concept of subjective well-being). In 1990 was a Fulbright scholar at the University of California, Los Angeles.

From 1977 to 1996 Hox was Assistant Professor at the University of Amsterdam at the department of Gerard de Zeeuw. In 1997 he was appointed Professor of Social Science Methodology at the Faculty of Social Sciences of the Utrecht University, which he started with the inaugural lecture, entitled “nieuws onder de zon: nieuwe oplossingen voor oude problemen” (There is nothing new under the sun: new solutions to old problems). One of his PhD students is Ger Snijkers. Hox also participates in the Interuniversity Graduate School of Psychometrics and Socio Metrics (IOPS) and chaired the Netherlands Organization for Social-Methodological Research (NOSMO).

Seminar Audience

This course is intended for PhD or MSc students and researchers with a basic background in statistics, who want to apply and understand multilevel models for grouped or longitudinal data. Participants can come from a variety of fields, including psychology, sociology, economics, or other disciplines with an interest in empirical data. A basic understanding of statistical inference, and some experience with analysis of variance and multiple regression analysis are prerequisites.

Participants are requested to bring their own laptop computer. The course will use the software HLM in the computer labs: a student version of HLM can be downloaded on Most techniques covered in this course can be applied in other statistical packages. Participants who own a statistical package that supports multilevel regression (SAS, SPSS, Stata) may use that, but will receive limited support in the computer lab.


The textbook used is J.J. Hox (2010) Multilevel Analysis. Techniques and Applications. NY: Routledge. Some additional material is made available during class.

Joop Hox Multilevel Modeling for Grouped & Longitudinal Data