Introduction to Meta‐Analysis

By M. Borenstein, L. Hedges, Julian P. T. Higgins, H. Rothstein. International Coaching Psychology Review, 2009

7,029 citations recorded by the source corpus.

Subfields: Public Health, Environmental and Occupational Health

View Paper: https://www.semanticscholar.org/paper/143de8c3b60ab558aeb7d5f9c5eb9aa85f4de449

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In Public Health, Environmental and Occupational Health

Citations in the corpus

Beyond cold technology: A systematic review and meta-analysis on emotions in technology-based learning environments (2018, methodology): “As WFM has not been developed for RVE meta-analysis, we created new datasets containing one weighted mean effect size and sampling variance per study (following Borenstein, Hedges, Higgins, & Rothstein, 2009; see Supplementary Material for details).”
A Guide to Conducting a Meta-Analysis with Non-Independent Effect Sizes (2019, methodology): “average the effect sizes within a study and use this figure in subsequent meta-analyses (Borenstein et al., 2009).”
Closed doors everywhere? A meta-analysis of field experiments on ethnic discrimination in rental housing markets (2018, background): “To allow additional interpretations, some effects were converted to response differences that measure the differences in the proportion of (positive) responses to the majority versus minority group (Borenstein et al. 2009, 48).”
The impact of flipped classrooms on student achievement in engineering education: A meta‐analysis of 10 years of research (2019, methodology): “With the exception of the study of high-school engineering by Chao et al. (2015), all other studies were conducted in higher education contexts. Various engineering disciplines were involved in the articles reviewed, including mechanical engineering (e.g., Cook, Han, Shuman, & Mason, 2017; Schrlau, ”
Living the good life: A meta-analysis of authenticity, well-being and engagement (2020, background): “Cumulative analysis can show whether there is ‘drift’ in effect sizes with publication year (i.e. time lag bias or drift toward lower effect size over time) or precision (i.e. whether the inclusion of smaller studies results in bias) (Borenstein et al., 2009b).”
Accurately measuring willingness to pay for consumer goods: a meta-analysis of the hypothetical bias (2019, background): “Accordingly, it applies to studies that measure the same outcome on different scales (Borenstein et al. 2009, p. 25).”
A Meta-Analysis of the Relationship Between Sleep Problems and Loneliness (2020, methodology): “When sufficient data were available (i.e., at least six samples with metrics of interest for categorical moderators; Borenstein et al., 2009) and models yielded a significant effect, univariate metaregression analyses were used to examine whether variability in effect sizes was accounted for by…”
The Why and How of the Integrative Review (2020, background): “At times, however, the two devices have been pitted against one another (Aguinis et al., 2011; Borenstein et al., 2009; Shapiro, 1994) in a false dichotomy.”
Beyond valence: a meta-analysis of discrete emotions in firm-customer encounters (2019, neutral): “The reliability-adjusted Fisher z-scores were then weighed with their inverse variance in order to give more weight to more precise effect size estimates (Borenstein et al. 2013).”