Biostatistics Daniel 9th Edition Pdf
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daniel malinsky’s methodological research focuses mostly on causal inference: developing statistical methods and machine learning tools to support inference about treatment effects, interventions, and policies. current research topics include graphical structure learning (a.k.a. causal discovery or causal model selection), semiparametric inference, time series analysis, and missing data. application areas of particular interest include environmental determinants of health and health disparities. dr. malinsky also studies algorithmic fairness: understanding and counteracting the biases introduced by data science tools deployed in socially-impactful settings. finally, dr.
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