PPT-Exploring Epidemiologic and Econometric Approaches to Causal Inference

Exploring Epidemiologic and Econometric Approaches to Causal Inference SERdigital March 9 2017 Miguel Hernán departments of epidemiology and biostatistics Causal inference from observational data. 1093panmpr013 Causal Inference without Balance Checking Coarsened Exact Matching Stefano M Iacus Department of Economics Business and Statistics University of Milan Via Conservatorio 7 I20124 Mila Epidemiology . matters: a new introduction to methodological foundations. Chapter . 8. Seven steps. Define . the population of . interest. Conceptualize . and create measures of exposures and health indicators. Jean-Philippe Pellet. Andre . Ellisseeff. Presented by Na Dai. Motivation. Why structure . l. earning?. What are Markov blankets?. Relationship between feature selection and Markov blankets?. Previous work. Inference on Causal Effects in aGeneralized Regression Kink DesignIZA DP No. 8757David CardDavid S. LeeZhuan PeiAndrea Weber Inference on Causal Effects in aGeneralized Regression Kink DesignDavid Car Susan Athey, Stanford GSB. Based on joint work with Guido Imbens, Stefan Wager. References outside CS literature. Imbens and Rubin Causal Inference book (2015): synthesis of literature prior to big data/ML. Peter Spirtes. Carnegie Mellon University. With slides from Lizzie Silver. Outline. Biology. Data and Background Knowledge. Problems. Algorithms. Causal Graph. gene protein. mRNA mRNA . protein gene. Kenneth A. Frank . Guan Saw, UT San Antonio. AERA workshop April 4, 2014 (. AERA on-line video – cost is $95. ). Motivation . Statistical inferences are often challenged because of uncontrolled bias. There may be bias due to uncontrolled confounding . Austin Nichols (Abt) & Linden McBride (Cornell). July 27, 2017. Stata Conference. Baltimore, MD. Overview. Machine learning methods dominant for classification/prediction problems.. Prediction is useful for causal inference if one is trying to predict propensity scores (probability of treatment conditional on observables);. Alex . Dimakis. UT Austin. j. oint work with . Murat . Kocaoglu. , . Karthik. . Shanmugam. Sriram. . Vishwanath. , . Babak. . Hassibi. Overview. Discovering causal directions . Part 1: . Interventions. Sciences: QUICK EXAMPLES. #. konfoundit. Kenneth A. . Frank. Ran . Xu; Zixi . Chen. ; I-Chien Chen, Guan Saw. 2018. (. AERA on-line video – cost is . $105. ). Motivation . Statistical inferences are often challenged because of uncontrolled bias. There may be bias due to uncontrolled confounding . Sciences: QUICK EXAMPLES. #. konfoundit. Kenneth A. . Frank. Ran . Xu; Zixi . Chen. ; I-Chien Chen, Guan Saw. 2018. (. AERA on-line video – cost is . $105. ). Motivation . Statistical inferences are often challenged because of uncontrolled bias. There may be bias due to uncontrolled confounding . Alex . Dimakis. UT Austin. j. oint work with . Murat . Kocaoglu. , . Karthik. . Shanmugam. Sriram. . Vishwanath. , . Babak. . Hassibi. Overview. Discovering causal directions . Part 1: . Interventions. to Causation. What is a Cause?. Merriam-Webster Dictionary. : Something that brings about a result especially a person or thing that is the agent of bringing something about.. KJ Rothman. : An event, condition, or characteristic without which the disease would not have occurred.. Chiu RW, Chim SS, Tong Y, Fung KS, Chan P, Zhao G, et al. Tracing SARS-Coronavirus Variant with Large Genomic Deletion. Emerg Infect Dis. 2005;11(1):168-170. https://doi.org/10.3201/eid1101.040544.