The data were analysed using conditionallogisticregression.
使用条件逻辑回归对数据进行分析。
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Results Univariable ConditionalLogisticRegression produces 21 significant risk factors, 7 main risk factors are finally filtered out by multivariable ConditionalLogisticRegression.
结果单因素分析筛选出21个统计意义的可疑因素,多因素逐步回归共筛选出7个主要的危险因素。
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If the NB conditional independence assumption actually holds, a Naive Bayes classifier will converge quicker than discriminative models like logisticregression, so you need less training data.