Mixed Linear Models

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Mixed Linear ModelsPE&RC logo klein transparant_2.png

Thursday 13 and Friday 14 June 2024

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)
Prior knowledge Knowledge of Basic Statistics and Linear Models and some experience with the software package R are assumed
Location Wageningen Campus, Building Forum, Room B0771
Accommodation Accommodation is not included in the fee of the course, but there are several possibilities in Wageningen. For non-WUR PE&RC members 50% of the accommodation costs can be reimbursed with a maximum of €30,- per night, please contact the PE&RC Office (office.pe@wur.nl) for more information.
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 are a number of groups on Facebook where students announce subrent possibilities and things like that. Examples include: Wageningen Room Subrent, Wageningen Room Sublets, Room Rent Wageningen, and Wageningen Student Plaza. Note that besides the restaurants in Wageningen, there are also options to have dinner on Wageningen Campus.

 

Fees 1
  EARLY-BIRD FEE 2 REGULAR FEE 2
PE&RC / WIMEK / VLAG / WIAS / WASS / EPS PhD candidates with an approved TSP and EngD candidates € 110,- € 160-
PE&RC postdocs and staff € 220,- € 270,-
All other academic participants € 260,- € 310,-
Non-academic participants € 480,- € 530,-

1 The course fee includes a digital reader.
2 The Early-Bird Fee applies to anyone who REGISTERS ON OR BEFORE 13 April 2024

  • If you need an invoice to complete your payment, please send an email to office.pe@wur.nl, including ALL relevant details that should be mentioned on the invoice (e.g., purchase order no., specific addresses, attendees, etc.).
  • The Early-Bird policy is such that the moment of REGISTRATION (and not payment) is leading for determining the fee that applies to you.
  • Please make sure that your payment is arranged within two weeks after your registration.
  • It is the participant's responsibility to make sure that he/she (or his/her secretary) completes the payment correctly and in time.
 
PE&RC Cancellation Conditions
  • Up to 4 (four) weeks prior to the start of the course, cancellation is free of charge.
  • Up to 2 (two) weeks prior to the start of the course, 50% of the participation fee will be charged.
  • In case of cancellation within two weeks prior to the start of the course or no show, 100% of the participation fee will be charged.

Note: If you would like to cancel your registration, ALWAYS inform us (and do note that you will be kept to the cancellation conditions)

More information

Dr. Gerrit Gort
Phone: +31 (0) 317 483570
Email: gerrit.gort@wur.nl

Claudius van de Vijver (PE&RC)
Phone: +31 (0) 317 485116
Email: claudius.vandevijver@wur.nl

Registration

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Please specify all relevant details that should be mentioned on the invoice (e.g., purchase order no., specific addresses, attendees, email contact person)