期刊
JOURNAL OF QUANTITATIVE CRIMINOLOGY
卷 38, 期 2, 页码 323-341出版社
SPRINGER/PLENUM PUBLISHERS
DOI: 10.1007/s10940-021-09494-w
关键词
Effect size; Incident rate ratio; Poisson; Counts; Meta-analysis; Cohen’ s d; Odds ratio
Area-based prevention studies often use count-based outcomes represented in a 2-by-2 table, with an emphasis on incident rate ratio and relative incident rate ratio as the preferred effect size, rather than Cohen's d or odds ratio. This approach is advocated for impact evaluations and meta-analyses of such studies.
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.
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