Meta-Analysis withR

By I. J. P. Howard. 2015

657 citations recorded by the source corpus.

This book provides a comprehensive introduction to performing meta-analysis using the statistical software R. It is intended for quantitative researchers and students in the medical and social sciences who wish to learn how to perform meta-analysis with R. As such, the book introduces the key concepts and models used in meta-analysis. It also includes chapters on the following advanced topics: publication bias and small study effects; missing data; multivariate meta-analysis, network meta-analysis; and meta-analysis of diagnostic studies.

Subfields: Artificial Intelligence, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/9e4f2caf9674570a0bd46c0f03232dae845dc9a3

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Jessica Mercader Ruiz
2. Dénes Szűcs
3. Irene Mammarella
4. Enrico Toffalini
5. S. Caviola
6. D. Giofrè

In Statistics and Probability

1. Jessica Mercader Ruiz
2. Dénes Szűcs
3. Irene Mammarella
4. Enrico Toffalini
5. S. Caviola
6. D. Giofrè
7. Usha Goswami

Citations in the corpus

• Math Performance and Academic Anxiety Forms, from Sociodemographic to Cognitive Aspects: a Meta-analysis on 906,311 Participants (2021, methodology): “The analytic strategy adopted in this meta-analysis followed the guidelines proposed by Borenstein et al. (2009), as well as Schwarzer et al. (2015).”