Poisson Regression for Modeling Count and Frequency Outcomes in Trauma Research
Poisson Regression for Modeling Count and Frequency Outcomes in Trauma Research
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DOI：
10.1002/jts.20359
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发表时间：
2008-10-01
影响因子：
3.3
通讯作者：
Taft, Casey T.
中科院分区：
文献类型：
--
作者：
Gagnon, David R.;Doron-LaMarca, Susan;Taft, Casey T.
作者描述了Poisson回归分析方法在创伤研究中的应用。创伤研究的结果可能代表在给定时间间隔内发生的行为事件的数量，例如身体攻击或药物滥用行为。传统的回归方法假设一个正态分布的结果变量，在预测变量的范围内具有等方差，并且可能不是对计数结果建模的最佳方法。泊松回归的应用程序，提出了使用数据从研究中的男性患者在酒精治疗计划和他们的女性伴侣的亲密伴侣的侵略。对Poisson回归模型和线性回归模型的结果进行了比较。
The authors describe bow the Poisson regression method for analyzing count or frequency outcome variables can be applied in trauma studies. The outcome of interest in trauma research may represent a count of the number of incidents of behavior occurring in a given time interval, such as acts of physical aggression or substance abuse. Traditional regression approacbes assume a normally distributed outcome variable with equal variances over the range of predictor variables, and may not be optimal for modeling count outcomes. An application Poisson regression is presented using data from a study of intimate partner agression among male patients in an alcohol treatment program and their female partners. Results of Poisson regression and linear regression models are compared.