Data Inference in Observational Settings

Peter Davis is Director of the COMPASS Research Centre and Professor of Sociology at the University of Auckland, with cross-appointments in the School of Population Health and in the Department of Statistics, also at the University of Auckland. Previously he served as Professor of Public Health at the University of Otago′s Christchurch School of Medicine. Davis specialises in medical sociology, and has achieved international recognition in his field, having worked as a consultant for the World Health Organisation. His main interests are in research methods, social structures, and policy, particularly health policy and health services. He has collaborated with colleagues in health research and in social statistics on a number of major surveys since the 1970s. He was Senior Editor (Health Policy) at the international journal, Social Science and Medicine, until 2012.

While causal thinking is at the heart of social science research and explanation, too little rigorous attention is paid by researchers as how to strengthen claims of causality.  This comprehensive collection draws together some of the best papers that point to the challenges of establishing causality and provide ways of addressing many of these challenges. It provides the resources to help both researchers and students address the question of causality much more systematically and convincingly than is often the case.

• VOLUME ONE: BACKGROUNDPART ONE: CAUSAL INFERENCE FROM OBSERVATIONAL DATAEstimating Causal Effects of Treatments in Randomized and Non-Randomized Studies - Donald Rubin Statistics and Causal Inference - Paul Holland Misunderstandings between Experimentalists and Observationalists about Causal Inference - Kosuke Imai et alThe Estimation of Causal Effects from Observational Data - Christoper Winship and Stephen Morgan Causal Inferences in Sociological Research - Markus Gangl PART TWO: POTENTIAL OUTCOMES AND COUNTERFACTUALSOn the Application of Probability Theory to Agricultural Experiments - Jerry Splawa-Neyman, D. Dabrowski and T. Speed Essay on Principles: Section NineCausal Inference Using Potential Outcomes - Donald Rubin Design, Modeling, DecisionsCounterfactuals and Hypothesis-Testing in Political Science - James Fearon Counterfactuals, Causal Effect Heterogeneity and the Catholic School Effect on Learning - Stephen Morgan Does Marriage Reduce Crime? A Counterfactual Approach to within-Individual Causal Effects - Robert Sampson et alPART THREE: PROGRAMME AND POLICY EVALUATIONReforms as Experiments - Donald Campbell Evaluating the Econometric Evaluations of Training Programs with Experimental Data - Robert LaLondeChoosing among Alternative Non-Experimental Methods for Estimating the Impact of Social Programs - James Heckman and V. Joseph Hotz The Case of Manpower TrainingEstimating the Effects of Potential Public Health Interventions on Population Disease Burden - Jennifer Ahern et alA Step-by-Step Illustration of Causal Inference MethodsThe Credibility Revolution in Empirical Economics - Joshua Angrist and Jörn-Steffen Pischke How Better Research Design Is Taking the Con out of EconometricsVOLUME TWO: ANALYTICAL TECHNIQUESPART FOUR: MATCHING METHODSThe Effectiveness of Adjustment by Subclassification in Removing Bias in Observational Studies - W. Cochran Reducing Bias in Observational Studies Using Subclassification on the Propensity Score - Rubin Rosenbaum Matching with Multiple Controls to Estimate Treatment Effects in Observational Studies - Herbert Smith Matching Estimators of Causal Effects - Stephen Morgan and David Harding Prospects and Pitfalls in Theory and PracticeMatching Methods for Causal Inference - Elizabeth Stuart A Review and a Look forwardPART FIVE: PROPENSITY SCORINGThe Central Role of the Propensity Score in Observational Studies for Causal Effects - Paul Rosenbaum and Donald Rubin Propensity Score-Matching Methods for Non-Experimental Causal Studies - Rajeev Dehejia and Sadek Wahba Too Much Ado about Propensity Score Models? Comparing Methods of Propensity Score Matching - Onur Baser A Comparison of the Ability of Different Propensity Score Models to Balance Measured Variables between Treated and Untreated Subjects - Peter Austin et al A Monte Carlo StudySelection Bias in Web Surveys and the Use of Propensity Scores - Matthias Schonlau et alPART SIX: CAUSAL DIAGRAMSCorrelation and Causation - Sewall Wright Structural Equation Methods in the Social Sciences - Arthur Goldberger Causal Diagrams for Empirical Research - Judea Pearl From Causal Diagrams to Birth Weight-Specific Curves of Infant Mortality - Sonia Hernandez-Diaz et al Neighborhood Effects in Temporal Perspective - Geoffrey Wodtke et alThe Impact of Long-Term Exposure to Concentrated Disadvantage on High School GraduationVOLUME THREE: TEMPORAL RELATIONSPART SEVEN: PANEL STUDIESCausal Inference from Panel Data - David Heise Panel Data to Estimate Effects of Events - Paul Allison The Impact of Incarceration on Wage Mobility and Inequality - Bruce Western Panel Models in Sociological Research - Charles Halaby Theory into PracticeCorrelation or Causation? Income Inequality and Infant Mortality in Fixed Effects Models in the Period 1960-2008 in 34 OECD Countries - Mauricio Avendano PART EIGHT: FAMILY STUDIESSibling Models and Data in Economics - Zvi Griliches Beginnings of a SurveyFraternal Resemblance in Education Attainment and Occupational Status - Robert Hauser and Peter Mossel Is Biology Destiny? Birth Weight and Life Chances - Dalton Conley and Neil Bennett Schooling or Social Origin? The Bias in the Effect of Educational Attainment on Social Orientations - Inge Sieben and Paul de Graaf Social Science Methods for Twins Data - Hans-Peter Kohler et alIntegrating Causality, Endowments and HeritabilityPART NINE: INSTRUMENTAL VARIABLESProblems with Instrumental Variables Estimation When the Correlation between the Instruments and the Endogeneous Explanatory Variable Is Weak - John Bound et alIdentification of Causal Effects Using Instrumental Variables - Joshua Angrist et alThe Colonial Origins of Comparative Development - Daron Acemoglu et alAn Empirical InvestigationA Genetic Instrumental Variables Analysis of the Effects of Prenatal Smoking on Birth Weight - George Wheby et alEvidence from Two SamplesInstrumental Variables in Sociology and the Social Sciences - Kenneth BollenVOLUME FOUR: EXPERIMENTAL ANALOGUESPART TEN: THE EXPERIMENTAL PARADIGMCausal Inference from Randomized Trials in Social Epidemiology - Jay Kaufman et alWhat Do Randomised Studies of Housing Mobility Demonstrate? Causal Inference in the Face of Interference - Michael Sobel Three Conditions under Which Experiments and Observational Studies Produce Comparable Causal Estimates - Thomas Cook et alNew Findings from within-Study ComparisonsThe Impact of Elections on Co-peration - Guy Grossman and Delia Baldassarri Evidence from a Lab-in-the-Field Experiment in UgandaNeighborhood Effects on Long-Term Well-Being of Low-Income Adults - Jens Ludwig et alPART ELEVEN: REGRESSION DISCONTINUITYRegression-Discontinuity Analysis - Donald Thistlethwaite and Donald Campbell An alternative to the ex post facto ExperimentAssignment to a Treatment Group on the Basis of a Covariate - Donald Rubin Capitalizing on Non-Random Assignment to Treatments - Richard Berk and David Rauma A Regression-Discontinuity Evaluation of a Crime-Control ProgramIdentification and Estimation of Local Average Treatment Effects - Guido Imbens and Joshua Angrist An Evaluation of California′s Inmate Classification System Using a Generalized Regression Discontinuity Design - Richard Berk and Jan de Leeuw PART TWELVE: QUASI-EXPERIMENTS AND NATURAL EXPERIMENTSMinimum Wages and Employment - David Card and Alan Krueger A Case Study of the Fast-Food Industry in New Jersey and PennsylvaniaNatural and Quasi-Experiments in Economics - Bruce Meyer How Much Should We Trust Differences-in-Differences Estimates? - Marianne Bertrand et alA Natural Experiment on Residential Change and Recidivism - David Kirk Lessons from Hurricane KatrinaEffects of Prenatal Poverty on Infant Health - Kate Strully et alState-Earned Income Tax Credits and Birth Weight