The logistic regression analysis of psychiatric data.
The logistic regression analysis of psychiatric data.
复制标题
精神病学数据的逻辑回归分析。
DOI：
10.1016/0022-3956(86)90003-8
复制
发表时间：
1986
影响因子：
4.8
通讯作者：
A. Dubro
中科院分区：
文献类型：
--
作者：
J. Fleiss;Janet B W Williams;A. Dubro
逻辑回归是一种选择的统计方法，用于分析自变量对二元因变量的影响，根据其在两个类别中的一个类别与另一个类别的概率。该方法必须通过计算机应用，并以DSM-III现场试验的数据进行了说明。因变量是以行为为导向的心理治疗与以精神分析为导向的心理治疗，自变量是一些患者和临床医生的特征。与普通多元回归一样，该方法既能分析分类变量，也能分析连续自变量。与应用于二进制数据的普通多元回归不同，逻辑回归分析必然产生介于0和1之间的估计概率。定义了由逻辑回归分析得出的关联度量，即比值比。提出并说明了对其进行推理的方法。
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.