Correcting the Effect Size of d for Range Restriction and Unreliability
By Philip Bobko, Philip L. Roth, C. Bobko. 2001
87 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Sociology and Political Science
View Paper: https://www.semanticscholar.org/paper/9db95e44810a65dec993b10d531936ec09d74e5a
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In Computer Networks and Communications
In Sociology and Political Science
- Gert G. Wagner
- Jürgen Schupp
- U. Schimmack
- Gilles E. Gignac
- C. Cliffordson
- Alastair Henry
- Armin Falk
- M. Kernis
Citations in the corpus
- At what sample size do latent variable correlations stabilize? (2018, background): “However, the impact of reliability would be expected to extend to other effect sizes (e.g., Cohen’s d; Bobko, Roth & Bobko, 2001). can impact the power of a statistical test (Beckstead, 2013; Cole & Preacher, 2014; Cleary & Linn, 1969; Goodwin & Leech, 2006; Sutcliffe, 1958)3.”
- Does College Teach Critical Thinking? A Meta-Analysis (2016, background): “As a result, effect size estimates may be downwardly biased by range restriction, a statistical artifact that results from artificially reduced variance in the outcome of interest (e.g., Bobko et al., 2001).”
- Motivation, Gender, and Possible Selves (2013, methodology): “The factor loading for GEN on Inter was 0.27 and the effect size, calculated in accordance with the method outlined by Bobko, Roth, and Bobko (2001), is indicative of a substantial difference: d = 0.56.”
- The Influence of Environment and Personality on the Affective and Cognitive Component of Subjective Well-being (2008, background): “This effect size can be corrected for unreliability in the CWB measure ( Bobko et al. 2001 ), which yields an effect size measure of d = 1.04.”
- Improving fluid intelligence with training on working memory: a meta-analysis (2014, unknown): “…this is effective in reducing test – retest practice effects, an unfortunate consequence is a reduction in measurement reliability (Jaeggi et al., 2014), which also causes downward biases in ES due to an increase in error variance that weakens the strength of its correlations (Bobko et al., 2001).”