APTS Statistical Modelling

Ioannis Kosmidis

Professor of Statistics
Department of Statistics, University of Warwick

ikosmidis.com   ikosmidis ikosmidis_

19 April 2024

Course content

  • Model selection

  • Beyond generalized linear models

  • Nonlinear models


Materials Link
Preliminary material ikosmidis.com/files/APTS-SM-Preliminary
Notes ikosmidis.com/files/APTS-SM-Notes
Slides: Introduction ikosmidis.com/files/APTS-SM-Slides-intro
Slides: Model selection ikosmidis.com/files/APTS-SM-Slides-model-selection
Slides: Beyond GLMs ikosmidis.com/files/APTS-SM-Slides-beyond-glms
Slides: Nonlinear models ikosmidis.com/files/APTS-SM-Slides-nonlinear-models
Slides: Latent variables ikosmidis.com/files/APTS-SM-Slides-latent
Lab 1 ikosmidis.com/files/APTS-SM-Notes/lab1.html
Lab 2 ikosmidis.com/files/APTS-SM-Notes/lab2.html

Space and time

Room Building
Lectures A09 ESLC (54)
Labs C19 Coates (36)
Breakouts C01, C13 ESLC (54)
Lunch Foyer ESLC (54)

Reproducible code

The notes and the slides have chunks of R code, which should be fully reproducible if executed in in the order they appear, in a single R session from

  • a standard R installation with
  • the contributed packages MuMIn, modelsummary, lme4, ggplot2, SMPracticals

In order to install those packages click on the arrow below and copy and pages the R code

install.packages(c("MuMIn", "modelsummary", "lme4", "ggplot2","SMPracticals"))

Typos and other contributions

Let me know (either during the lectures or by email) if you find any tyops on the slides, or any of the other materials.

I would welcome contributions of code that replicates the analyses in the notes in other languages (e.g. Python, Julia).


  • I will be making time for questions.

  • Lift your hand or speak up at any point.