Meta-analysis in Biology and Environmental Science



Course Dates

Students admitted / Credit Points

The registration is closed

UFZ Leipzig

March 14-18, 2016; 9:30 am - 4:30 pm

24 students /

2 ECTS credits


Meta-analysis is the statistical synthesis of the results of different research studies. These tools and the conceptual framework in which they are based provide a widely implemented, cross-disciplinary statistical framework for quantifying, pooling, and evaluating the results of different studies on the same topic. Meta-analysis is firmly established in medical and social sciences research, and has become an important statistical approach in the fields of ecology, evolution and environmental sciences in recent decades. This course will cover the framework of meta-analysis specifically as it is being used in the biological and environmental sciences. In this course, students will learn how to conduct a meta-analysis from the start to finish, including formulating hypotheses, extracting data from primary literature, computing effect sizes, testing for the effects of covariates (moderators of explanatory variables), examining assumptions and sources of bias, and presenting the results.. We will also discuss some common mistakes as well as controversies regarding the implementation of meta-analysis in the biological and environmental sciences.

The course will be taught full-time during one week. Each day during the course will include both theoretical lectures and extensive hands-on experience with practical assignments and group projects.



After completion of the course, the participants are expected to be able to

 1.      Knowledge and understanding

 -Define meta-analysis and describe its role in the research process

 -Demonstrate how to assess and interpret variation in effect size across studies


2.      Skills and abilities

 -List and perform the different steps included in a meta-analysis

 -Compute effect sizes and treatment effects

 -Compare fixed- and random effect models for synthesizing data


3.      Judgement and approach

 -Explain how to avoid common mistakes in meta-analysis

 -Identify controversies in meta-analysis


Lecturer in charge

Prof. Jessica Gurevitch, Stony Brook University, USA


Further lecturers

Prof. Julia Koricheva, University of London, UK


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