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逻辑回归中的可替换权重。

Fungible weights in logistic regression.

机构信息

Korn Ferry.

Department of Psychology, University of Minnesota-Twin Cities.

出版信息

Psychol Methods. 2016 Jun;21(2):241-60. doi: 10.1037/met0000060. Epub 2015 Dec 14.

Abstract

In this article we develop methods for assessing parameter sensitivity in logistic regression models. To set the stage for this work, we first review Waller's (2008) equations for computing fungible weights in linear regression. Next, we describe 2 methods for computing fungible weights in logistic regression. To demonstrate the utility of these methods, we compute fungible logistic regression weights using data from the Centers for Disease Control and Prevention's (2010) Youth Risk Behavior Surveillance Survey, and we illustrate how these alternate weights can be used to evaluate parameter sensitivity. To make our work accessible to the research community, we provide R code (R Core Team, 2015) that will generate both kinds of fungible logistic regression weights. (PsycINFO Database Record

摘要

在本文中,我们开发了用于评估逻辑回归模型中参数敏感性的方法。为了开展这项工作,我们首先回顾了 Waller(2008)用于计算线性回归中可互换权重的方程。接下来,我们描述了两种用于计算逻辑回归中可互换权重的方法。为了展示这些方法的实用性,我们使用疾病控制与预防中心(2010)的青年风险行为监测调查的数据计算了可互换逻辑回归权重,并说明了如何使用这些替代权重来评估参数敏感性。为了使我们的工作能够为研究界所接受,我们提供了 R 代码(R Core Team,2015),该代码将生成两种可互换逻辑回归权重。(PsycINFO 数据库记录

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