Meta-analysis in psychology and neuroscience: Approaches and applications - Einzelansicht

All the materials and more information about participation/exam will be on Moodle. In case of questions, please contact linda.ficco@uni-jena.de.

The selected literature will be available on Moodle soon.

For those students who want to get started before the seminar begins, optional resources are listed below.

For effect-size meta-analyses:

Cochrane Training | Trusted evidence. Informed decisions. Better health.

Deeks, J. J., Higgins, J. P., Altman, D. G., & Cochrane Statistical Methods Group. (2019). Analysing data and undertaking meta‐analyses. Cochrane handbook for systematic reviews of interventions, 241-284.

Baldwin, S. A., & Shadish, W. R. (2011). A primer on meta-analysis in clinical psychology. Journal of Experimental Psychopathology, 2(2), 294-317.

Welcome! | Doing Meta-Analysis in R (bookdown.org)

Schwarzer, G., Carpenter, J. R., & Rücker, G. (2015). Meta-analysis with R (Vol. 4784). Cham: springer.

For neuroimaging meta-analyses:

Radua, J., & Mataix-Cols, D. (2012). Meta-analytic methods for neuroimaging data explained. Biology of mood & anxiety disorders, 2(1), 1-11.

Fox, P. T., Lancaster, J. L., Laird, A. R., & Eickhoff, S. B. (2014). Meta-analysis in human neuroimaging: computational modeling of large-scale databases. Annual review of neuroscience, 37, 409-434.

This seminar contributes 3 ECTS to students' academic curricula. Students who attend the seminar without taking the examination are required to participate actively to sessions and to do one presentation. 

For those students who plan to take the exam, this will be in written format. More details about the exam modalities will be posted on Moodle and will be discussed during the seminar directly with the students.

Meta-analysis is a category of statistical techniques that allow a quantitative integration of results from individual empirical studies. These techniques have become increasingly important in medicine and psychology during the past four decades, given their usefulness in generating scientific consensus, resolving open discrepancies and asking research questions that go beyond those of single experimental works (Baldwin et al, 2011; Higgins et al., 2019). More recently, similar approaches have been developed in the context of neuroimaging literature, where meta-analyses are used to investigate the neural underpinnings of cognitive processes by estimating a convergence of results across many studies (Radua & Mataix-Cols, 2012; Eickhoff & Bzdok, 2013; Fox et al., 2014). However, in order to achieve a critical understanding of the results published in a meta-analytic work, it is crucial to become aware of the variety of available approaches and their limitations (LeLoriel, 1997). Thus in this methodological seminar, students will read, present and discuss both theoretical and practical articles about meta-analyses.

The first part of the seminar will be focussed on introducing the methodological aspects of effect-size meta-analyses, their use in psychology and their criticisms (Borenstein et al., 2009). This will include a practical simulation of a "toy" meta-analysis, to familiarize the students with the procedure and the potential challenges of performing a meta-analysis. Instead, in the second part the focus will be on neuroimaging meta-analyses, where the students will be shortly introduced to neuroimaging data analysis (Lindquist, 2008), and they will learn the differences and commonalities with the classical type (e.g. Stevens & Hamann, 2012; Darda & Ramsey, 2019).

References:

Baldwin S, Shadish W. A Primer on Meta-analysis in Clinical Psychology. Journal of Experimental Psychopathology (2011). Vol 2 (2), 294-317. 10.5127/jep.009610

Borenstein M, Hedges LV, Higgins LPT, Rothstein HR, Introduction to Meta-Analysis (2009). John Wiley & Sons, 978-0-470-05724-7

Darda KM & Ramsay R, The inhibition of automatic imitation: A meta-analysis and synthesis of fMRI studies (2019). NeuroImage, Vol 197, 320-329.

Eickhoff SB and Bzdok D, Meta-Analyses in Basic and Clinical Neuroscience: State of the Art and Perspective (2013). Springer-Verlag Berlin Heidelberg. 

Fox PT, Lancaster JL, Laird AR and Eickhoff SB, Meta-Analysis in Human Neuroimaging: Computational Modeling of Large-Scale Databases (2014). The Annual Review of Neuroscience, Vol 37, 409-234. 

Higgins JPT, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, Welch VA (editors). Cochrane Handbook for Systematic Reviews of Interventions, version 6.0, www.training.cochrane.org/handbook.

LeLoriel J, Gregoire G, Benhaddad A, Lapierre J and Derderian F. (1997) Discrepancies between meta-analyses and subsequent large randomized, controlled trials. The New Englan Journal of Medicine , Vol 337 (8), 536-542.

Lindquist, M. A. (2008). The statistical analysis of fMRI data. Statistical Science, 23(4), 439-464.

Radua J & Mataix-Cols D, Meta-analytic methods for neuroimaging data explained (2012). Biology of Mood & Anxiety Disorders, Vol 2(6), 1-11. 

Stevens JS & Hamman S, Sex differences in brain activation to emotional stimuli: A meta-analysis of neuroimaging studies (2012). Neuropsychologia, Vol 50, 1578– 1593.

This seminar is designed for an audience of students at the Master level, who have an interest in learning the methodological aspects, as well as the limitations and potentials of meta-analyses. In particular, the second section of the seminar requires basic knowledge about neuroscience and neuroimaging. 

Although the seminar has a cognitive neuroscience focus, students from all Psychology M.Sc. programs, as well as Medicine and students from social sciences are welcome to join. In case the requests for participation exceed the maximum number of available spots, priority will be given on an individual basis. Higher priority will be given to international students, students with disabilities, students who are closer to studies completion.