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The Role of Exchangeability in Inference

https://doi.org/10.1214/aos/1176345331
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Outgoing claims: the papers this work cites, builds on, or argues with.

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Causality, Conditional Probability, and Control
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A paradox in the interpretation of group comparisons.
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Statistical adjustments when comparing preexisting groups.
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Estimating causal effects of treatments in randomized and nonrandomized studies.
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Antecedent probability and the efficiency of psychometric signs, patterns, or cutting scores.
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Spurious Correlation: A Causal Interpretation*
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On Simpson's Paradox and the Sure-Thing Principle
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Bayesian Inference for Causal Effects: The Role of Randomization
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Analysis of Covariance: A Delicate Instrument
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A Probabilistic Theory of Causality.
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Properties of Diagnostic Data Distributions
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The Foundations of Statistical Inference.

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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The Use of Statistical Methods in Management Research: Suggestions from a Case Study
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How Much Terror? Dissidents, Governments, Institutions and the Cross-National Study of Terror Attacks
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Understanding Simpson's Paradox
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Multivariate Analysis, B ayesian
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Exchangeability
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Randomization
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Bayesian Analysis for the Social Sciences
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ON LORD'S PARADOX
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INTEGRATING COGNITIVE AND PSYCHOMETRIC MODELS TO MEASURE DOCUMENT LITERACY
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EVIDENCE AND INFERENCE IN EDUCATIONAL ASSESSMENT1,2
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Design and Analysis of Vaccine Studies
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Exchangeability
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Methodology and Epistemology of Multilevel Analysis
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General Conclusion
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Conditional Independence in Statistics
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Permutation Statistical Methods
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Exchangeability
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Mining Association Rules from Database Tables with the Instances of Simpson’s Paradox
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Probleme bei der Interpretation von geschlechtersegregierten Daten am Beispiel von Simpsons Paradoxon
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A Probabilistic Model for Heterogeneous Populations and Related Burn-in Design Problems
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Exchangeability
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The Epistemic Approach: Subjectivist Interpretation
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The Epistemic Approach: Logicist Interpretation
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Conclusion to Part II
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Causal Tendency: A Review
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Bayesianism and Causality, or, Why I am Only a Half-Bayesian
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Real-World Implications of a Methodological Dilemma: Endogenous Confounding in Causal Decomposition Analysis
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Evidence and Inference in Educational Assessment
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Randomization in experimental science
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Yule–Simpson’s paradox: the probabilistic versus the empirical conundrum
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Some collapsibility results for n-dimensional contingency tables
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A New Condition for Transitivity of Probabilistic Support
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The logic of Simpson’s paradox
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Comments on: Panel data analysis—advantages and challenges
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Exchangeable mortality projection
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Bayesian reduced rank multigroup regression analysis: a new model for multigroup data with hybrid parameter sharing
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Exchangeability and its economic applications
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Remarks on the role of conditional probability in data exploration
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On exchangeable sampling distributions for uncontrolled data
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Randomization in a bayesian perspective
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Linear Hypothesis: Fallacies and Interpretive Problems (Simpson's Paradox)
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Causal Inference
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Linear Hypothesis: Fallacies and Interpretive Problems (Simpson's Paradox)
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Data aggregation and Simpson’s paradox gauged by index numbers
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Aggregation of comparisons data and reversal phenomena of metrological interest
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Wavelets and functional magnetic resonance imaging of the human brain
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A comparison of permutation and parametric testing for between group effective connectivity differences using DCM
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Informative allocation and consistent treatment selection
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Cost overruns in transportation infrastructure projects: Sowing the seeds for a probabilistic theory of causation
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The implications of Simpson's paradox for cross-scale inference among lakes
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Bayesian predictiveness, exchangeability and sufficientness in bacterial taxonomy
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The effects of customer service, branding, and price on the perceived value of local telephone service
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24 Statistical Inference for Causal Effects, with Emphasis on Applications in Psychometrics and Education
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2 Statistical Inference for Causal Effects, With Emphasis on Applications in Epidemiology and Medical Statistics
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Statistical Inference as Severe Testing
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Preface
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Beyond Probabilism and Performance
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Error Probing Tools versus Logics of Evidence
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Induction and Confirmation
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Falsification, Pseudoscience, Induction
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Ingenious and Severe Tests
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It’s The Methods, Stupid
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Capability and Severity: Deeper Concepts
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The Myth of “The Myth of Objectivity”
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Rejection Fallacies: Who’s Exaggerating What?
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Auditing: Biasing Selection Effects and Randomization
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More Auditing: Objectivity and Model Checking
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Power: Pre-data and Post-data
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How Not to Corrupt Power
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Deconstructing the N-P versus Fisher Debates
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What Ever Happened to Bayesian Foundations?
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Pragmatic and Error Statistical Bayesians
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Souvenirs
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Index
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Newcomb's Problem
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Introduction
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Does Newcomb’s Problem Actually Exist?
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Newcomb’s Problem, Rationality, and Restraint
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The “Why Ain’cha Rich?” Argument
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Epistemic Time Bias in Newcomb’s Problem∗
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Newcomb’s Problem is Everyone’s Problem: Making Political and Economic Decisions when Behavior is Interdependent
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Success-First Decision Theories
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Deliberation and Stability in Newcomb Problems and Pseudo-Newcomb Problems1
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“Click!” Bait for Causalists
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Game Theory and Decision Theory (Causal and Evidential)
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Diagnosing Newcomb’s Problem with Causal Graphs
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References
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Simpson's Paradox and Related Phenomena
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Using Bayesian statistical modelling as a bridge between quantitative and qualitative analyses: illustrated via analysis of an online teaching tool
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How Cognitive Science Challenges the Educational Measurement Tradition∗
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Statistical Modeling of Spatially Stratified Heterogeneous Data
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The Role of Randomization in Inference
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Experimental concepts for testing probabilistic earthquake forecasting and seismic hazard models
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The Simpson's paradox unraveled
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Critical Appraisal of Studies Using Laboratory Animal Models
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Simpson's Paradox in Psychology
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Causation and Statistical Inference
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Reconciling Conflicting Gauss-Markov Conditions in the Classical Linear Regression Model
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Evidentiary Foundations of Mixture Item Response Theory Models
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Data exploration and conditional probability
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Incompletely specified probabilistic networks
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Optimal Bayesian Randomization
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Bayesian Nonparametric Inference for Random Distributions and Related Functions
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Regressions, Short and Long
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Isolating the effect of rater experience as a time‐variant predictor of performance ratings
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Ensuring Valid Inference for Cox Hazard Ratios After Variable Selection
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Discussion of the Paper by Draper, Hodges, Mallows and Pregibon
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Unexpected Pathways Through Education: Why Do Some Students Not Succeed in School and What Helps Others Beat the Odds?
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Integrating Cognitive and Psychometric Models to Measure Document Literacy
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RIM: A Random Item Mixture Model to Detect Differential Item Functioning
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Seeing and Doing: The Concept of Causation
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Conditional Independence in Statistical Theory
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Assessing Sensitivity to an Unobserved Binary Covariate in an Observational Study with Binary Outcome
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Testing Collapsibility in Contingency Tables
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Specious rules: an efficient and effective unifying method for removing misleading and uninformative patterns in association rule mining
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Comment: Understanding Simpson’s Paradox
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Six Statistical Senses
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The Rise of Markov Chain Monte Carlo Estimation for Psychometric Modeling
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Diagnostico medico: modelagens e metodos
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Inferência para o modelo Bernoulli na presença de adversários
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Formas finitas do teorema de de finetti: a visao, preditivista da inferencia estatistica em populacoes finitas
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Addressing Selection and Confounding Biases in Dental Claims Data: A Causal Inference Framework for Periodontal–Systemic Disease Research
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Burden of Proof/Burden of Remedy
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Disaggregating Homicide: Changing Trends in Subtypes over Time
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Subjective and Objective Methods of Evaluating Social Programs
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Hospital-wide Mortality as a Quality Metric
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Wavelets and statistical analysis of functional magnetic resonance images of the human brain
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