Meta analysis

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Meta-analysis

To be announced

Scope

Researchers trying to summarize the constantly growing body of published research are increasingly using meta-analysis. The focus of this 2-day course will be on concepts of linear models and mixed linear models in meta-analysis. The statistical software R will be used.

Programme

Day 1

  1. Introduction
    • Why perform a meta-analysis
    • Main steps of a meta-analysis
  2. Estimation of effect sizes of treatments
    • Effect sizes for continuous and categorical data (mean difference, odds ratio, etc.)
    • Estimation using linear and generalized linear fixed-effect models
    • Estimation using linear and generalized linear mixed-effect models
    • Sensitivity and uncertainty analysis of the estimated effect sizes
  3. Practical session 1
    • Analysis of a dataset by the participants using R
    • Discussion of the results

Day 2

  1. Regression methods for estimating relationships between variables
    • Definitions
    • Regression using linear, generalized linear, and nonlinear fixed-effect models
    • Regression using linear, generalized linear, and nonlinear mixed-effect models
    • Sensitivity and uncertainty analysis for regression models
  2. Practical session 2
    • Analysis of a dataset by the participants using R
    • Discussion of the results
  3. Quality criteria
    • Definitions of quality criteria
    • Assessment of a large number of meta-analyses
  4. Discussion and conclusion
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 every two years (Summer)
Number of credits 0.6 ECTS
Lecturers Dr. David Makowski (Department of Environment & Agronomy, INRA AgroParisTech), Dr. Gerrit Gort (Biometris, Wageningen University)
Prior knowledge Basic knowledge of statistical methods at the graduate level (e.g., regression, ANOVA, hypothesis testing). Basic knowledge of linear, generalized linear, and mixed models. Familiarity with the statistical software R is advisable, as examples and exercises will be presented in R, and it is assumed that participants have working knowledge of R for applying these.
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. 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

Lennart Suselbeek (PE&RC)
Phone: +31 (0) 317 485426
Email: lennart.suselbeek@wur.nl

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.

 
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