Meta-Analysis and Subgroups
By M. Borenstein, Julian P. T. Higgins. Prevention Science, 2013
663 citations recorded by the source corpus.
Subfields: Cell Biology, Pharmacology, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/56a73188ff532771d31868af852190051bff4b81
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Cell Biology
In Pharmacology
In Statistics and Probability
- Michael J. Valenzuela
- Joseph P. Mazer
- San Bolkan
- Alan K. Goodboy
- Harry Hallock
- A. Lampit
- Scott Titsworth
- S. Myers
Citations in the corpus
- Computerized Cognitive Training in Cognitively Healthy Older Adults: A Systematic Review and Meta-Analysis of Effect Modifiers (2014, methodology): “In the third stage, subgroup analyses were based on a mixed-effects model, which uses a random-effects model to generate within-subgroup variance and a fixed-effects model to compare effects between subgroups [34].”
- Two Meta-analyses Exploring the Relationship between Teacher Clarity and Student Learning (2015, methodology): “Because the moderators were coded as dichotomous groups, subgroup analyses were conducted (Borenstein & Higgins, 2013) by computing omnibus tests of between-groups differences (QB) for mixed-effects models (Hedges & Pigott, 2004).”
- What Is the Evidence for Physical Therapy Poststroke? A Systematic Review and Meta-Analysis (2014, neutral): “In addition, the observational nature of the subgroup analyses means they should be interpreted with caution, as it is known that subgroup analyses in meta-analyses can be less highly powered than analyses for main effects [29,579,580].”