Gender Effects in the Peer Reviews of Grant Proposals: A Comprehensive Meta-Analysis Comparing Traditional and Multilevel Approaches

By Herbert W. Marsh, Lutz Bornmann, Rüdiger Mutz, Hans-Dieter Daniel, A. O’Mara. 2009

171 citations recorded by the source corpus.

Subfields: Education, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/bdfdb0de6e512a0c203f85789db1811c206c3338

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Citations in the corpus

Modeling dependent effect sizes with three-level meta-analyses: a structural equation modeling approach. (2014, methodology): “The second data set was based on Bornmann et al. (2007) and Marsh et al. (2009).”
A multidisciplinary survey on discrimination analysis (2013, methodology): “The subsequent study by Marsh (2009), using multilevel regression, revised the conclusion for research grant applications, but it remained the same for fellowship applications.”
Discovering Gender Discrimination in Project Funding (2012, methodology): “interesting methodology is meta-analysis [3], [24]: a regression model is not built from data on individual applications, but rather from aggregated data collected from other studies.”
A Review of Meta-Analyses in Education (2012, methodology): “Five meta-analyses using mixed-effects model provided the method for estimating between-study variance (i.e., methods of moments in Aloe & Becker, 2009b; Borman, Hewes, Overman, & Brown, 2003; Marsh et al., 2009; Murphy et al., 2009; and Bayesian method used in Rakes et al.,”
Women in Academic Science: Experimental Findings From Hiring Studies (2018, methodology): “However, Marsh et al. (2009) reanalyzed these data using a multilevel measurement model and arrived at a very different conclusion.”
Women in Academic Science (2014, background): “For example, the Massachusetts Institute of Technology (MIT) Report of the School of Humanities, Arts, and Social Sciences (2002, page 18) found that at MIT, an increase in salary “partly depends on obtaining outside offers from other universities, and such outside offers have become increasingly im”