Zero-inflated Models & GLMM using R

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Introduction to Zero Inflated GLMs and GLMMs with R

- Using frequentist tools -

To be announced


This online course consists of 5 modules representing a total of approximately 40 hours of work. Each module consists of video files with short theory presentations, followed by exercises using real data sets, and video files discussing the solutions. All video files are on-demand and can be watched online, as often as you want, at any time of the day, within a 6 month period.
A discussion board allows for daily interaction between instructors and participants. The course runs from 09.00-16.00h (CEST) using Live teaching via Zoom. You are invited to apply the statistical techniques discussed during the course on your own data and if you encounter any problems, you can ask questions on the Discussion Board. Included in the course fee is a 1-hour face-to face consultancy chat with the instructors in which you can discuss your own data.
This course is taught by Dr Alain Zuur and Dr Elena Ieno, who are the leading authorities in the world on the topic of zero-inflated models in R.


Course content

The course starts with a short revision of data exploration, multiple linear regression and Poisson GLM. We then discuss 3 more models for the analysis of count data, namely the negative binomial, generalised Poisson and Conway-Maxwell-Poisson GLMs. After a short theory presentation on zero-inflated models, we apply all four GLMs, and their zero-inflation cousins on various data sets. We also use the Tweedie GLM and the zero-altered Gamma GLM for the analysis of zero-inflated continuous data.
In the second part of the course, we start with a short revision of linear mixed-effects models. This is followed by a series of exercises in which we analyse zero-inflated count data, continuous data and proportional data using zero-inflated GLMMs.
Throughout the course we will use the glmmTMB package in R.

Module 1 consists of 6 on-demand videos

  • General introduction.
  • Short revision of data exploration and linear regression in R.
  • Introduction to matrix notation.
  • Revision Poisson GLM for the analysis of count data.
  • Introducing the negative binomial (NB), generalised Poisson (GP) and Conway-Maxwell-Poisson GLMs for the analysis of count data.
  • Model validation using DHARMa.

Module 2 consists of 4 on-demand videos

  • Theory presentation on zero-inflated models.
  • Three exercises using the zero-inflated Poisson, zero-inflated negative binomial, zero-inflated generalised Poisson and the zero-inflated Conway-Maxwell GLMs for the analysis of data sets with an excessive number of zeros in the count data.

Module 3 consists of 5 on-demand video files

  • Theory presentation on hurdle models for the analysis of zero-inflated count data. This presentation also covers zero-truncated models.
  • One exercise using zero-altered Poisson and zero-altered negative binomial models for the analysis of count data with an excessive number of zeros.
  • Theory presentation on the GLM with the Tweedie distribution.
  • Application of a Tweedie GLM on zero-inflated continuous data. We will also explain the zero-altered Gamma model.

Module 4 consists of 4 on-demand video files

  • Revision of linear mixed-effects models.
  • Exercise on linear mixed-effects models.
  • Exercise using a zero-inflated Poisson GLMM to analyse count data.
  • Exercise using a zero-inflated negative binomial GLMM to analyse count data.

Module 5 consisting of 4 on-demand video files

  • Exercise using a zero-inflated binomial GLMM to analyse proportional data with an excessive number of zeros.
  • Exercise using a zero-inflated beta GLMM to analyse proportional data with an excessive number of zeros.
  • Exercise using a Tweedie GLMM and a zero-altered Gamma GLMM to analyse continuous data with an excessive number of zeros.
  • What to present in a paper.

Free 1-hour face-to-face meeting
The course fee includes a 1-hour face-to-face meeting with one or both instructors. The meeting needs to take place within 6 months after the last live zoom meeting. You can discuss your own data, but we strongly advice that the statistical topics are within the content of the course. The 1-hour needs to be consumed in one session, and will take place at a mutual convenient time.

General information
Target Group The course is aimed at PhD candidates, postdocs, and other academics
Group Size No limitations
Course duration 5 days
Language of instruction English
Frequency of recurrence Once every 2 or 3 years
Number of credits 1.5 ECTS
Lecturers Dr Alain Zuur & Dr Elena Ieno (Highland Statistics Ltd.)
Prior knowledge Basic knowledge of R, working knowledge of data exploration and multiple linear regression. Knowledge of GLM is an advantage, but a revision exercise (with video file) of Poisson GLM and negative binomial GLM will be provided.
Recommended Literature Zuur, Ieno (2021). The World of Zero-Inflated Models. Volume 1: Using GLMs. Zuur, Ieno (2022). The World of Zero-Inflated Models. Volume 2: Using GLMM.
These books are available from from January 2022 (available from Books are not included in the course fee, the course can be followed without purchasing these books.
Terms and conditions Please click here for the terms and conditions for this course.
Location Online


Fees 1
PE&RC / WIMEK / WASS / EPS / VLAG / WIAS PhD candidates with an approved TSP € 275,- € 325,-
a) All other PhD candidates
b) Postdocs and staff of the above mentioned Graduate Schools
€ 590,- € 640,-
All others € 865,- € 915,-

1 The course fee includes course materials and a 1-hour face-to-face meeting with one or both instructors

More information

Dr Claudius van de Vijver (PE&RC)
Phone: +31 317 485116

Registration of interest

At this moment, this course is not scheduled yet. However, if you register your interest in this activity below, we will inform you as soon as the course is scheduled and registration of participation is opened.