RT Article
T1 The Relative Incident Rate Ratio Effect Size for Count-Based Impact Evaluations: When an Odds Ratio is Not an Odds Ratio
JF Journal of quantitative criminology
VO 38
IS 2
SP 323
OP 341
A1 Wilson, David B.
LA English
YR 2022
UL https://krimdok.uni-tuebingen.de/Record/1884549020
AB 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.
K1 odds ratio
K1 Cohen’s d
K1 Meta-analysis
K1 Counts
K1 Poisson
K1 Incident rate ratio
K1 effect size
DO 10.1007/s10940-021-09494-w