The data were analysed using conditional logistic regression.

使用条件逻辑回归对数据进行分析。

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Results Univariable Conditional Logistic Regression produces 21 significant risk factors, 7 main risk factors are finally filtered out by multivariable Conditional Logistic Regression.

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 logistic regression, so you need less training data.

倘若条件独立性假设确实满足，朴素贝叶斯分类器将会比判别模型，譬如逻辑回归收敛得更快，因此你只需要更少的训练数据。

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If the NB conditional independence assumption actually holds, a Naive Bayes classifier will converge quicker than discriminative models like logistic regression, so you need less training data.

倘若条件独立性假设确实满足，朴素贝叶斯分类器将会比判别模型，譬如逻辑回归收敛得更快，因此你只需要更少的训练数据。

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