PDF-(BOOS)-Observation and Experiment: An Introduction to Causal Inference

In the daily news and the scientific literature we are faced with conflicting claims about the effects caused by some treatments behaviors and policies A daily glass of wine prolongs life or so we are told Yet we are also told that alcohol can cause lifethreatening cancer and that pregnant women should abstain from drinking Some say that raising the minimum wage decreases inequality while others say it increases unemployment Investigators once confidently claimed that hormone replacement therapy reduces the risk of heart disease but today investigators confidently claim it raises that risk How should we study such questionsObservation and Experiment is an introduction to causal inference from one of the fields leading scholars Using minimal mathematics and statistics Paul Rosenbaum explains key concepts and methods through scientific examples that make complex ideas concrete and abstract principles accessibleSome causal questions can be studied in randomized trials in which coin flips assign individuals to treatments But because randomized trials are not always practical or ethical many causal questions are investigated in nonrandomized observational studies To illustrate Rosenbaum draws examples from clinical medicine economics public health epidemiology clinical psychology and psychiatry Readers gain an understanding of the design and interpretation of randomized trials the ways they differ from observational studies and the techniques used to remove investigate and appraise bias in observational studies Observation and Experiment is a valuable resource for anyone with a serious interest in the empirical study of human health behavior and wellbeing. 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 How we look at things in science. What is observation?. Observations are made in science. They are made by using: . Senses . Tools . increase accuracy & precision . Facts not opinions. . Two types of Observation. Warm up. Share your picture with the people at your table group.. Make sure you have your Science notebook, agenda and a sharpened pencil. use tape to put it in front of your table of contents. Describe the difference between observations and inferences. 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. Warm up. Share your picture with the people at your table group.. Make sure you have your Science notebook, agenda and a sharpened pencil. use tape to put it in front of your table of contents. Describe the difference between observations and inferences. 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 . What is observation?. Observations are made in science. They are made by using: . Senses . Tools . increase accuracy & precision . Facts not opinions. . Two types of Observation. Qua. l. itative. What is observation?. Observations are made in science. They are made by using: . The 5 Senses . Taste. Smell. Touch. Hear . See . Two types of Observation. Qua. l. itative. Qua. n. titative. 1. Qualitative . #1. The boy is in the water. . Observation. #2. The weather is cold. . . Inference. #3. The tree branch is broken. . Observation. #4. If the boy crawled out of the water, the goat would butt him. . Inference. 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.