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Meta-Analysis

  • 01 - 02 July 2020
  • Wageningen University
  • Methodology
  • 0.6 ECTS

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

Former occurrences of this course

4-5 July 2018   |   30 June – 1 July 2016   |   25-26 June 2015   |   23-24 June 2014   |   14-16 Nov 2012

  • PE&RC, Wageningen University
  • Once every two years (Summer)
  • 24 participants
  • 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.