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INTERACTION DETECTION FOR GENERALIZED LINEAR MODELS

机译:广义线性模型的交互检测

摘要

Provided are techniques for interaction detection for generalized linear models. Basic statistics are calculated for a pair of categorical predictor variables and a target variable from a dataset during a single pass over the dataset. It is determined whether there is a significant interaction effect for the pair of categorical predictor variables on the target variable by: calculating a log-likelihood value for a full generalized linear model without estimating model parameters; calculating the model parameters for a reduced generalized linear model with a recursive marginal mean accumulation technique using the basic statistics; calculating a log-likelihood value for the reduced generalized linear model; calculating a likelihood ratio test statistic using the log-likelihood value for the full generalized linear model and the log-likelihood value for the reduced generalized linear model; calculating a p-value of the likelihood ratio test statistic; and comparing the p-value to a significance level.
机译:提供了用于广义线性模型的交互检测的技术。在数据集的一次遍历过程中,从数据集中为一对分类预测变量和目标变量计算基本统计量。通过以下方法确定这对分类预测变量对目标变量是否存在显着的交互作用:计算一个完整的广义线性模型的对数似然值,而无需估计模型参数;使用基本统计量,通过递归边际均值累积技术,为简化的广义线性模型计算模型参数;计算简化的广义线性模型的对数似然值;使用完全广义线性模型的对数似然值和简化广义线性模型的对数似然值来计算似然比检验统计量;计算似然比检验统计量的p值;并将p值与显着性水平进行比较。

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