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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 ( IF 2.8 ) Pub Date : 2021-02-11 , DOI: 10.1007/s10940-021-09494-w
David B. Wilson

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.



中文翻译:

基于计数的影响评估的相对事件发生率比率效应大小:当赔率比率不是赔率比率时

基于区域的预防研究通常会产生可以2比2计数表表示的结果。例如,一张表可能显示干预前12个月期间的犯罪计数,而一个或多个治疗和控制区域的干预期间则为12个月。这种类型的研究已使用科恩氏d或优势比作为效应量指标。当用于此类数据时,前者不合适,而后者则是错误的称呼。在准泊松回归模型的基础上,开发了入射率比和相对入射率比效应量以及相关的超分散参数,并作为影响评估和荟萃分析中基于计数的结果的首选效应量。

更新日期:2021-02-11
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