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Conditional Independence in Statistical Theory
Abstract
Summary: Some simple heuristic properties of conditional independence are shown to form a conceptual framework for much of the theory of statistical inference. This framework is illustrated by an examination of the rôle of conditional independence in several diverse areas of the field of statistics. Topics covered include sufficiency and ancillarity, parameter identification, causal inference, prediction sufficiency, data selection mechanisms, invariant statistical models and a subjectivist approach to model-building.
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Cites
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Cited by
The central role of the propensity score in observational studies for causal effects
ROSENBAUM, P. R., & RUBIN, D. B. (1983) · Biometrika · doi:10.1093/biomet/70.1.41 · Cited by 31,241
(1988) · Cited by 16,582
Causation, Prediction, and Search
Spirtes, P., Glymour, C., & Scheines, R. (1993) · Lecture Notes in Statistics · doi:10.1007/978-1-4612-2748-9 · Cited by 4,617
Matching As An Econometric Evaluation Estimator
Heckman, J. J., Ichimura, H., & Todd, P. (1998) · Review of Economic Studies · doi:10.1111/1467-937x.00044 · Cited by 3,807
Reducing Bias in Observational Studies Using Subclassification on the Propensity Score
Rosenbaum, P. R., & Rubin, D. B. (1984) · Journal of the American Statistical Association · doi:10.1080/01621459.1984.10478078 · Cited by 3,082
Metadata
- Authors
- Dawid, A. P.
- Venue
- Journal of the Royal Statistical Society Series B: Statistical Methodology
- Publisher
- Oxford University Press (OUP)
- Published
- 1979-09-01
- Volume
- 41
- Issue
- 1
- Pages
- 1-15
- ISSN
- 1369-7412 (ISSN-L)
- 1467-9868
- OpenAlex
- W30853191
- Cited by
- 1,501
- References
- 3
- FWCI
- 3.92
- Type
- journal article
- Language
- en
- Open access
- closed
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