Conditional Independence in Statistical Theory
- 1 September 1979
- journal article
- research article
- Published by Oxford University Press (OUP) in Journal of the Royal Statistical Society Series B: Statistical Methodology
- Vol. 41 (1) , 1-15
- https://doi.org/10.1111/j.2517-6161.1979.tb01052.x
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.This publication has 25 references indexed in Scilit:
- Conditional Independence for Statistical OperationsThe Annals of Statistics, 1980
- Prediction Sufficiency When the Loss Function Does Not Depend on The Unknown ParameterThe Annals of Statistics, 1977
- Characterizations of Prediction Sufficiency (Adequacy) in Terms of Risk FunctionsThe Annals of Statistics, 1975
- BIAS IN SELECTIONJournal of Educational Measurement, 1973
- On Simpson's Paradox and the Sure-Thing PrincipleJournal of the American Statistical Association, 1972
- Some Problems in the Theory of Optimal Stopping RulesThe Annals of Mathematical Statistics, 1967
- Adequate Subfields and SufficiencyThe Annals of Mathematical Statistics, 1967
- On the Foundations of Statistical InferenceJournal of the American Statistical Association, 1962
- Sufficiency and Statistical Decision FunctionsThe Annals of Mathematical Statistics, 1954
- Identifiability of a Linear Relation between Variables Which Are Subject to ErrorEconometrica, 1950