A simple method for converting an odds ratio to effect size for use in meta-analysis.

By S. Chinn. 2000

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Citations in the corpus

Risk-Needs Assessment in Juvenile Justice (2011, methodology): “Using a conversion suggested by Chinn (2000) for effect sizes, we would consider ORs equal to 1.2 to 1.72 as small, 1.72 to 2.4 as moderate, and greater than 2.4 as large.”
Children Living Without Their Fathers: Population Estimates and Indicators of Educational Well-being (2008, background): “The odds ratio is the odds of one occurrence divided by the odds of another.) This effect sizes is small ( Chinn 2000; Cohen 1992).”
High School Socioeconomic Segregation and Student Attainment (2013, methodology): “Odds ratios are converted to Cohen’s d effect size using the method described by Chinn (2000). The sampling design described previously likely contributed to the pattern in these results.”
Synthesis without meta-analysis (SWiM) in systematic reviews: reporting guideline (2020, methodology): “An example of a statistical method to convert an odds ratio to a standardised mean diference is that proposed by Chinn (2000).21 For other methods and metrics, see Cochrane Handbook Chapter 6.22 Item 3: describe the synthesis methods Description Describe and justify the methods used to synthesise…”
A systematic review and meta-analysis of dietary patterns and depression in community-dwelling adults. (2014, methodology): “81 to convert them to log ORs and the corresponding SElog OR according to the Hasselblad and Hedges method (12, 13).”
Of guns and geese: a meta-analytic review of the ‘weapon focus’ literature (2013, background): “Hazell, O'Connell, Heathcote, Robertson, & Henry, 1995 ) recent theorists have recognized the benefits of aggregating these data into a single analysis (see Chinn, 2000 ; Lipsey & Wilson, 2000 ; Sanchez-Meca et al, 2003 ; Whitehead, Bailey, & Elbourne, 1999 ).”
Diagnosing Teachers’ Understandings of Rational Numbers: Building a Multidimensional Test Within the Diagnostic Classification Framework (2014, neutral): “The conventional metrics for evaluating the effect size of an odds ratio apply (see Chinn, 2000, where 1.44 < small < 2.47, 2.47 < medium < 4.25, and large > 4.25).”