When small effect sizes tell a big story, and when large effect sizes don't.
By Jose M. Cortina, Ronald S. Landis. 2009
173 citations recorded by the source corpus.
Subfields: Clinical Psychology, Economics and Econometrics, General Decision Sciences
View Paper: https://www.semanticscholar.org/paper/c6347aa66031785b37cb4128bf6db6f1f53295b3
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Clinical Psychology
- Sandra Costa
- Alexander S. Nassrelgrgawi
- Muhammad Ishtiaq Ali
- P. Neves
- Kevin J. Murphy
- Scott Tonidandel
- Christopher P. Cerasoli
- Peter A. Bamberger
In Economics and Econometrics
- P. Neves
- Kevin J. Murphy
- Steve Werner
- Scott Tonidandel
- Christopher P. Cerasoli
- Peter A. Bamberger
- James M. LeBreton
- Herman Aguinis
In General Decision Sciences
Citations in the corpus
- Board Age and Gender Diversity: A Test of Competing Linear and Curvilinear Predictions (2014, background): “economic impact of increased gender diversity is considerable (Cortina and Landis, 2009).”
- Determining the Relative Importance of Predictors in Logistic Regression: An Extension of Relative Weight Analysis (2010, background): “This definition of importance usually takes into account the effect size associated with a particular predictor, but it also must incorporate aspects of the situation to fully gauge practical importance (Cortina & Landis, 2009).”
- Audience Heterogeneity and the Effectiveness of Market Signals: How to Overcome Liabilities of Foreignness in Film Exports? (2014, unknown): “We contribute to research on market signals by shifting attention from producers and their use of 11 Documenting the substantive significance of our interactions is particularly important given the small statistical effect sizes (Prentice & Miller, 1992; Cortina & Landis, 2009).”
- Performance, incentives, and needs for autonomy, competence, and relatedness: a meta-analysis (2016, background): “…one finding in particular, that effect sizes were higher in published studies, reflecting a potential publication bias in the literature.3 This unfortunately means that researchers likely have to seek out and find large effect sizes to get primary research published (Cortina and Landis 2009).”
- Polluted work: A self-control perspective on air pollution appraisals, organizational citizenship, and counterproductive work behavior (2017, unknown): “…we contribute to the literatures on depletion, OCBs and CWBs by demonstrating that appraisals of the natural environment can meaningfully affect these phenomena on a daily basis, and by shifting focus from between-level sources of variance to daily, within-level variation (Cortina & Landis, 2009).”
- Signaling in Secret: Pay-for-Performance and the Incentive and Sorting Effects of Pay Secrecy (2014, background): “Moreover, particularly when it comes to task performance and the continuation intentions of employees, even small effects can be practically meaningful (Cortina & Landis, 2009; Prentice & Miller, 1992).”
- RWA Web: A Free, Comprehensive, Web-Based, and User-Friendly Tool for Relative Weight Analyses (2014, background): “Information regarding a variable’s contribution to predictable variance is helpful when considering the practical utility of a variable, but aspects of the particular situation must also be considered to fully gauge practical importance (Cortina and Landis 2009).”
- The ABC for Studying the Too-Much-of-a-Good-Thing Effect (2016, background): “Indeed, prior research has argued that in some research contexts, small effect sizes can be substantially meaningful (Cortina & Landis, 2009; LeBreton, Hargis, Griepentrog, Oswald, & Ployhart, 2007).”
- Customer-Centric Science: Reporting Significant Research Results With Rigor, Relevance, and Practical Impact in Mind (2010, background): “For a study to report results in a way that is customer-centric in terms of the needs of practitioners, it must contextualize and properly interpret the results and conclusions (cf. Cortina & Landis, 2009).”
- HARKing: How Badly Can Cherry-Picking and Question Trolling Produce Bias in Published Results? (2019, background): “However, the implications of our results regarding the damaging effects of HARKing for theory as well as practice necessitate that we place results within specific fields and research domains because in many cases, Bsmall^ effects make a big difference (Aguinis et al., 2010; Cortina & Landis, 2009).”
- The Too-Much-of-a-Good-Thing Effect in Management (2013, background): “Although an asymptotic relation is a smaller effect compared with a U-shaped relation, this does not mean that an asymptotic relation is necessarily less important for science and practice (Aguinis et al., 2010; Cortina & Landis, 2009).”
- Relative Importance Analysis: A Useful Supplement to Regression Analysis (2011, background): “Information regarding a variable’s contribution to predictable variance is helpful when considering the practical utility of a variable, but aspects of the particular situation must also be considered to fully gauge practical importance (Cortina and Landis 2009).”
- DOING GOOD, FEELING GOOD: EXAMINING THE ROLE OF ORGANIZATIONAL CITIZENSHIP BEHAVIORS IN CHANGING MOOD (2011, background): “As Cortina and Landis (2009) explain, small effect sizes need not always be indicative of weak results (see also Prentice & Miller, 1992).”
- Job insecurity and work outcomes: The role of psychological contract breach and positive psychological capital (2017, background): “However, these effects may suggest strong empirical evidence and impressive support for a given phenomenon (Cortina & Landis, 2009).”
- The impact of abusive supervision and co-worker support on hospitality and tourism student employees’ turnover intentions in Ecuador (2018, background): “Any departure from zero of the variance to be explained represents substantial evidence for the importance of the phenomenon in question (Cortina & Landis, 2009).”