Little attention has been devoted to framing multiple continuous social variables as a "mixture" for social epidemiologic analysis. We propose using the Bayesian kernel machine regression analytic framework that yields univariate, bivariate, and overall exposure mixture effects.

中文翻译：

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用于社会流行病学研究的贝叶斯核机器回归。


人们很少关注将多个连续社会变量构建为社会流行病学分析的“混合物”。我们建议使用贝叶斯核机器回归分析框架来产生单变量、双变量和整体暴露混合效应。