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精神科数据的逻辑回归分析。

The logistic regression analysis of psychiatric data.

作者信息

Fleiss J L, Williams J B, Dubro A F

出版信息

J Psychiatr Res. 1986;20(3):195-209. doi: 10.1016/0022-3956(86)90003-8.

Abstract

Logistic regression is presented as the statistical method of choice for analyzing the effects of independent variables on a binary dependent variable in terms of the probability of being in one of its two categories vs the other. The method, which must be applied by computer, is illustrated on data from the DSM-III field trials. The dependent variable is treatment with behaviourally-oriented psychotherapy vs treatment with psychoanalytically-oriented psychotherapy, and the independent variables are several patient and clinician characteristics. Like ordinary multiple regression, the method is shown capable of analyzing categorical as well as continuous independent variables. Unlike ordinary multiple regression when applied to binary data, logistic regression analysis necessarily yields estimated probabilities that lie between 0 and 1. The measure of association derived from logistic regression analysis, the odds ratio, is defined. Methods for making inferences about it are presented and illustrated.

摘要

逻辑回归作为一种统计方法被提出,用于分析自变量对二元因变量的影响,具体是根据处于其两个类别之一而非另一个类别的概率来进行分析。该方法必须通过计算机应用,并以DSM-III现场试验的数据为例进行说明。因变量是行为导向心理治疗与精神分析导向心理治疗,自变量是几个患者和临床医生的特征。与普通多元回归一样,该方法能够分析分类自变量和连续自变量。与应用于二元数据的普通多元回归不同,逻辑回归分析必然会得出介于0和1之间的估计概率。文中定义了从逻辑回归分析得出的关联度量——优势比,并给出并说明了对其进行推断的方法。

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