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Data Inference in Observational Settings
Four Volume Set
Edited by:
- Peter Davis - University of Auckland, New Zealand
December 2013 | 1 648 pages | SAGE Publications Ltd
Most social research is carried out in observational settings; that is, most social researchers collect information in the "real world" trying to do as little possible to alter the circumstances of study. However, there is a fundamental problem with this kind of research, in that it is very hard to draw "causal" conclusions, because of the complexity and obduracy of social reality. This is not just a problem for social scientists interested in policy or social action. It applies across the board more generally because it becomes difficult to know, without the conditions for credible inference, what conclusions can be drawn from any piece of empirical research that aspires to be anything more than descriptive of social phenomena.
This four-volume set of readings introduces the reader to the advances that have been made in trying to help social researchers draw more credible inferences from investigations carried out in observational settings. Drawing from a variety of sources - from logicians and philosophers, to applied statisticians, computer scientists and econometricians, to epidemiologists and social researchers - this collection provides an invaluable resource for scholars in the field.
Volume One: Background
Volume Two: Analytical Techniques
Volume Three: Temporal Relations
Volume Four: Experimental Analogues
VOLUME ONE: BACKGROUND
PART ONE: CAUSAL INFERENCE FROM OBSERVATIONAL DATA
Donald Rubin
Estimating Causal Effects of Treatments in Randomized and Non-Randomized Studies
Paul Holland
Statistics and Causal Inference
Kosuke Imai et al
Misunderstandings between Experimentalists and Observationalists about Causal Inference
Christoper Winship and Stephen Morgan
The Estimation of Causal Effects from Observational Data
Markus Gangl
Causal Inferences in Sociological Research
PART TWO: POTENTIAL OUTCOMES AND COUNTERFACTUALS
Jerry Splawa-Neyman, D. Dabrowski and T. Speed
On the Application of Probability Theory to Agricultural Experiments
Donald Rubin
Causal Inference Using Potential Outcomes
James Fearon
Counterfactuals and Hypothesis-Testing in Political Science
Stephen Morgan
Counterfactuals, Causal Effect Heterogeneity and the Catholic School Effect on Learning
Robert Sampson et al
Does Marriage Reduce Crime? A Counterfactual Approach to within-Individual Causal Effects
PART THREE: PROGRAMME AND POLICY EVALUATION
Donald Campbell
Reforms as Experiments
Robert LaLonde
Evaluating the Econometric Evaluations of Training Programs with Experimental Data
James Heckman and V. Joseph Hotz
Choosing among Alternative Non-Experimental Methods for Estimating the Impact of Social Programs
Jennifer Ahern et al
Estimating the Effects of Potential Public Health Interventions on Population Disease Burden
Joshua Angrist and Jörn-Steffen Pischke
The Credibility Revolution in Empirical Economics
VOLUME TWO: ANALYTICAL TECHNIQUES
PART FOUR: MATCHING METHODS
W. Cochran
The Effectiveness of Adjustment by Subclassification in Removing Bias in Observational Studies
Rubin Rosenbaum
Reducing Bias in Observational Studies Using Subclassification on the Propensity Score
Herbert Smith
Matching with Multiple Controls to Estimate Treatment Effects in Observational Studies
Stephen Morgan and David Harding
Matching Estimators of Causal Effects
Elizabeth Stuart
Matching Methods for Causal Inference
PART FIVE: PROPENSITY SCORING
Paul Rosenbaum and Donald Rubin
The Central Role of the Propensity Score in Observational Studies for Causal Effects
Rajeev Dehejia and Sadek Wahba
Propensity Score-Matching Methods for Non-Experimental Causal Studies
Onur Baser
Too Much Ado about Propensity Score Models? Comparing Methods of Propensity Score Matching
Peter Austin et al
A Comparison of the Ability of Different Propensity Score Models to Balance Measured Variables between Treated and Untreated Subjects
Matthias Schonlau et al
Selection Bias in Web Surveys and the Use of Propensity Scores
PART SIX: CAUSAL DIAGRAMS
Sewall Wright
Correlation and Causation
Arthur Goldberger
Structural Equation Methods in the Social Sciences
Judea Pearl
Causal Diagrams for Empirical Research
Sonia Hernandez-Diaz et al
From Causal Diagrams to Birth Weight-Specific Curves of Infant Mortality
Geoffrey Wodtke et al
Neighborhood Effects in Temporal Perspective
VOLUME THREE: TEMPORAL RELATIONS
PART SEVEN: PANEL STUDIES
David Heise
Causal Inference from Panel Data
Paul Allison
Panel Data to Estimate Effects of Events
Bruce Western
The Impact of Incarceration on Wage Mobility and Inequality
Charles Halaby
Panel Models in Sociological Research
Mauricio Avendano
Correlation or Causation? Income Inequality and Infant Mortality in Fixed Effects Models in the Period 1960-2008 in 34 OECD Countries
PART EIGHT: FAMILY STUDIES
Zvi Griliches
Sibling Models and Data in Economics
Robert Hauser and Peter Mossel
Fraternal Resemblance in Education Attainment and Occupational Status
Dalton Conley and Neil Bennett
Is Biology Destiny? Birth Weight and Life Chances
Inge Sieben and Paul de Graaf
Schooling or Social Origin? The Bias in the Effect of Educational Attainment on Social Orientations
Hans-Peter Kohler et al
Social Science Methods for Twins Data
PART NINE: INSTRUMENTAL VARIABLES
John Bound et al
Problems with Instrumental Variables Estimation When the Correlation between the Instruments and the Endogeneous Explanatory Variable Is Weak
Joshua Angrist et al
Identification of Causal Effects Using Instrumental Variables
Daron Acemoglu et al
The Colonial Origins of Comparative Development
George Wheby et al
A Genetic Instrumental Variables Analysis of the Effects of Prenatal Smoking on Birth Weight
Kenneth Bollen
Instrumental Variables in Sociology and the Social Sciences
VOLUME FOUR: EXPERIMENTAL ANALOGUES
PART TEN: THE EXPERIMENTAL PARADIGM
Jay Kaufman et al
Causal Inference from Randomized Trials in Social Epidemiology
Michael Sobel
What Do Randomised Studies of Housing Mobility Demonstrate? Causal Inference in the Face of Interference
Thomas Cook et al
Three Conditions under Which Experiments and Observational Studies Produce Comparable Causal Estimates
Guy Grossman and Delia Baldassarri
The Impact of Elections on Co-peration
Jens Ludwig et al
Neighborhood Effects on Long-Term Well-Being of Low-Income Adults
PART ELEVEN: REGRESSION DISCONTINUITY
Donald Thistlethwaite and Donald Campbell
Regression-Discontinuity Analysis
Donald Rubin
Assignment to a Treatment Group on the Basis of a Covariate
Richard Berk and David Rauma
Capitalizing on Non-Random Assignment to Treatments
Guido Imbens and Joshua Angrist
Identification and Estimation of Local Average Treatment Effects
Richard Berk and Jan de Leeuw
An Evaluation of California's Inmate Classification System Using a Generalized Regression Discontinuity Design
PART TWELVE: QUASI-EXPERIMENTS AND NATURAL EXPERIMENTS
David Card and Alan Krueger
Minimum Wages and Employment
Bruce Meyer
Natural and Quasi-Experiments in Economics
Marianne Bertrand et al
How Much Should We Trust Differences-in-Differences Estimates?
David Kirk
A Natural Experiment on Residential Change and Recidivism
Kate Strully et al
Effects of Prenatal Poverty on Infant Health
