Mixed Linear Models
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Mixed Linear Models
To be announced
Scope
In this module we discuss how to analyse dependent data, that is, data for which the assumption of independence needed in Linear Models is violated. So: Do you have a nested experimental set-up? Like measurements on large plots, but also on smaller plots within the larger plots? Do you have repeated measurements? Like measurements on height of the same plant over time? Or weight of the same animal over time? Do you have pseudo-replication? Like measuring 3 plants from the same pot? In this sort of situations it is not reasonable to use ordinary ANOVA or regression to analyse your data. These methods are likely too optimistic, and you will get erroneous significant results. And your paper will be returned for, hopefully, a major revision! With mixed linear models a more appropriate model, allowing for dependence between observations, can be specified, which will lead to more reasonable conclusions.
In this module, you will learn about these models (also about the formulation in matrix notation, covariance matrices included), about the way to fit them to your data using software, and about the output produced by the software. In computer sessions participants can practice fitting models of this type, and gain an understanding of the output created by the software. You are encouraged to bring along your own data if you have any. The main statistical software used in this course is R.
Programme
- Day 1, morning: Gentle introduction to mixed models
- Day 1, afternoon: General theory of mixed models, examples of some variance components models with R
- Day 2, morning: Estimation and testing in a mixed model
- Day 2, afternoon: Repeated measurements with examples in R
General information
| Target Group | The course is aimed at PhD candidates and other academics |
| Group Size | 24 participants |
| Course duration | 2 days |
| Language of instruction | English |
| Frequency of recurrence | Once a year (Summer) |
| Number of credits | 0.6 ECTS |
| Lecturers | Dr. Gerrit Gort (Biometris, Wageningen University), Dr. Bas Engel (Biometris, Wageningen University) |
| Prior knowledge | Knowledge of Basic Statistics and Linear Models and some experience with the software package R are assumed |
| Location | Wageningen University Campus |
| Options for accommodation | Accommodation is not included in the fee of the course, but there are several possibilities in Wageningen. For information on B&B's and hotels in Wageningen please visit proefwageningen.nl. Another option is Short Stay Wageningen. Furthermore Airbnb offers several rooms in the area. Finally, there is also a very active public Facebook group called “Wageningen Student Plaza”, where rooms are often offered for short-term sublets, but where one could also easily post a request for renting a room for a week in Wageningen. Finally, note that besides the restaurants in Wageningen, there are also options to have dinner at Wageningen Campus. |
More information
Claudius van de Vijver (PE&RC)
Phone: +31 (0) 317 485116
Email: claudius.vandevijver@wur.nl
Registration
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.