Do logistic regression and signal detection identify different subgroups at risk? Implications for the design of tailored interventions.
Do logistic regression and signal detection identify different subgroups at risk? Implications for the design of tailored interventions.
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逻辑回归和信号检测是否可以识别面临风险的不同亚组？
DOI：
10.1037/1082-989x.6.1.35
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发表时间：
2001
期刊：
影响因子：
--
通讯作者：
Taylor,CB
中科院分区：
文献类型：
--
作者：
Kiernan,M;Kraemer,HC;Winkleby,MA;King,AC;Taylor,CB
Identifying subgroups of high-risk individuals can lead to the development of tailored interventions for those subgroups. This study compared two multivariate statistical methods (logistic regression and signal detection) and evaluated their ability to identify subgroups at risk. The methods identified similar risk predictors and had similar predictive accuracy in exploratory and validation samples. However, the 2 methods did not classify individuals into the same subgroups. Within subgroups, logistic regression identified individuals that were homogeneous in outcome but heterogeneous in risk predictors. In contrast, signal detection identified individuals that were homogeneous in both outcome and risk predictors. Because of the ability to identify homogeneous subgroups, signal detection may be more useful than logistic regression for designing distinct tailored interventions for subgroups of high-risk individuals.(PsycINFO Database Record (c) 2016 APA, all rights reserved)
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