'Causal effect' diaporamas de présentation

Chapter 9 Causal Inference and Marginal Structural Models

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Propensity Score Analysis A tool for causal inference in non-randomized studies

Propensity Score Analysis A tool for causal inference in non-randomized studies. Summer Statistics Workshop 2010 Felix Thoemmes Texas A&M University. Agenda. Motivating examples Definition of causal effects with potential outcomes Definition of propensity scores

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Wisconsin Scholars Longitudinal Study: An Introduction

Wisconsin Scholars Longitudinal Study: An Introduction. SARA GOLDRICK-RAB & DOUGLAS N. HARRIS Co-Directors University of Wisconsin-Madison WWW.FINAIDSTUDY.ORG. Thanks for the Extensive Support!. Funders: Bill and Melinda Gates Foundation, William T. Grant Foundation, Spencer Foundation

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Access Networks: Applications and Policy

Access Networks: Applications and Policy. Nick Feamster CS 6250 Fall 2011. (HomeOS slides from Ratul Mahajan). Huge amount of tech in homes. Home users struggle. Management Nightmare. Integration Hurdles. Why developers are not helping. Vendors only build islands.

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Research Design

Research Design. Jean Yoon December 15, 2010. Outline. Causality and study design Quasi-experimental methods for observational studies Covariate matching Differences-in-differences Regression discontinuity. Outline. Causality and study design

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External validity: to what populations do our study results apply ?

External validity: to what populations do our study results apply ? . Epidemiology matters: a new introduction to methodological foundations Chapter 12. Seven steps. Define the population of interest Conceptualize and create measures of exposures and health indicators

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Causal Diagrams and the Identification of Causal Effects

Causal Diagrams and the Identification of Causal Effects. A presentation of Chapters 3 and 4 of: Judea Pearl Causality: Models, Reasoning and Inference Cambridge University Press, 2000. An Example. This is example is due to Cochran through Pearl [2000, p.66]

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Rules for Causal Graphs

Rules for Causal Graphs. References: Causality: Models, Reasoning and Inference by Judea Pearl - chapter 3 (2000) Causal diagrams for empirical research by Judea Pearl, Biometrika 82:669-710 (1995). Example of Causal Graph. Cd4 is confounding effect of medical risk.

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Is the association causal, or are there alternative explanations?

Is the association causal, or are there alternative explanations? . 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

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Africa RISING M&E Expert Meeting Addis Ababa, 5-7 September 2012

Africa RISING M&E Expert Meeting Addis Ababa, 5-7 September 2012. Monitoring and Evaluation (M&E) strategy. Outline. Timeline Objectives of M&E Targeting vs Research Monitoring and Evaluation Theory of Change Evaluation designs Open issues. Timeline. Component Inventory.

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Causal Model Ying Nian Wu UCLA Department of Statistics July 13, 2007 IPAM Summer School

Causal Model Ying Nian Wu UCLA Department of Statistics July 13, 2007 IPAM Summer School. Observational study --- observed relationship may not be cause-effect Example: people who sleep 7 hours report better health. sleep 7 hrs (vs 8 hrs). health. health. sleep 7 hrs (vs 8 hrs).

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Matthew Samore, MD VA Salt Lake City Health Care System Professor of Internal Medicine

Experience in improving healthcare decision-making with health IT: integrating theory, research, and practice. Matthew Samore, MD VA Salt Lake City Health Care System Professor of Internal Medicine Adjunct Professor of Biomedical Informatics University of Utah. Acknowledgments.

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Unit A2.1 Causality

Unit A2.1 Causality. Kenneth D. Forbus Qualitative Reasoning Group Northwestern University. Overview. What is causality? Design choices for causality in qualitative physics Using causality Example: Self-explanatory simulators. A qualitative physics view of causation.

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Differences-in-Differences

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Randomization

Randomization. Objective. To estimate the causal effect of intervention on the treated We need A good counterfactual (control group). Illustration. Program impact. Effect of exogenous factors. Motivation.

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LT5: Review

LT5: Review. Sam Marden s.h.marden@lse.ac.uk. 1. Working with summary data. Parts (a) and (b) describe the data. For parts (c) and (d) you will need to recall that the t-statistic is calculated as

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Difference-in-Difference

Difference-in-Difference. Development Workshop. Typical problem in proving causal effects. U sing differences to estimate causal effects in experimental data (treatment+control groups)

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Larysa Minzyuk - Felice Russo

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Methods and Approaches to investigate the UK Education System

Methods and Approaches to investigate the UK Education System. Sandra McNally, University of Surrey and Centre for Economic Performance, London School of Economics. Overview. Some questions addressed in the CEP Education Programme Data Core methodological issues.

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