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The Relative Incident Rate Ratio Effect Size for Count-Based Impact Evaluations: When an Odds Ratio is Not an Odds Ratio

Journal of quantitative criminology, 2022-06, Vol.38 (2), p.323-341 [Peer Reviewed Journal]

The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature 2021 ;The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature 2021. ;ISSN: 0748-4518 ;EISSN: 1573-7799 ;DOI: 10.1007/s10940-021-09494-w

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  • Title:
    The Relative Incident Rate Ratio Effect Size for Count-Based Impact Evaluations: When an Odds Ratio is Not an Odds Ratio
  • Author: Wilson, David B.
  • Subjects: Crime ; Crime prevention ; Criminology and Criminal Justice ; Intervention ; Law and Criminolgy ; Meta-analysis ; Methodology of the Social Sciences ; Original Paper ; Prevention ; Sociology ; Statistics
  • Is Part Of: Journal of quantitative criminology, 2022-06, Vol.38 (2), p.323-341
  • Description: Area-based prevention studies often produce results that can be represented in a 2-by-2 table of counts. For example, a table may show the crime counts during a 12-month period prior to the intervention compared to a 12-month period during the intervention for a treatment and control area or areas. Studies of this type have used either Cohen’s d or the odds ratio as an effect size index. The former is unsuitable and the latter is a misnomer when used on data of this type. Based on the quasi-Poisson regression model, an incident rate ratio and relative incident rate ratio effect size and associated overdispersion parameter are developed and advocated as the preferred effect size for count-based outcomes in impact evaluations and meta-analyses of such studies.
  • Publisher: New York: Springer US
  • Language: English
  • Identifier: ISSN: 0748-4518
    EISSN: 1573-7799
    DOI: 10.1007/s10940-021-09494-w
  • Source: ProQuest One Psychology
    AUTh Library subscriptions: ProQuest Central

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