Rubin’s rules for combining multiple imputation estimates
E1181894
UNEXPLORED
Rubin’s rules for combining multiple imputation estimates are a set of statistical formulas that specify how to pool parameter estimates and standard errors across multiple imputed datasets to obtain valid overall inferences.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Rubin’s rules for combining multiple imputation estimates canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T15878955 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rubin’s rules for combining multiple imputation estimates Context triple: [Donald B. Rubin, knownFor, Rubin’s rules for combining multiple imputation estimates]
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A.
A Solution to the Ecological Inference Problem
A Solution to the Ecological Inference Problem is a influential methodological book by political scientist Gary King that introduces statistical techniques for inferring individual-level behavior from aggregate data.
-
B.
“Statistical Confluence Analysis by Means of Complete Regression Systems”
“Statistical Confluence Analysis by Means of Complete Regression Systems” is a foundational econometric work by Ragnar Frisch that develops a systematic regression-based framework for analyzing interdependent economic relationships.
-
C.
The Theory of Confounding
The Theory of Confounding is a foundational chapter in R.A. Fisher’s work on experimental design that explains how to manage and interpret the mixing of treatment effects with nuisance factors in statistical experiments.
-
D.
Bayesian model averaging
Bayesian model averaging is a statistical technique that combines predictions from multiple models by weighting them according to their posterior probabilities to account for model uncertainty.
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E.
Generalized method of moments
The generalized method of moments is an econometric estimation technique that uses sample moments to infer model parameters without requiring full specification of the underlying probability distribution.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Rubin’s rules for combining multiple imputation estimates Target entity description: Rubin’s rules for combining multiple imputation estimates are a set of statistical formulas that specify how to pool parameter estimates and standard errors across multiple imputed datasets to obtain valid overall inferences.
-
A.
A Solution to the Ecological Inference Problem
A Solution to the Ecological Inference Problem is a influential methodological book by political scientist Gary King that introduces statistical techniques for inferring individual-level behavior from aggregate data.
-
B.
“Statistical Confluence Analysis by Means of Complete Regression Systems”
“Statistical Confluence Analysis by Means of Complete Regression Systems” is a foundational econometric work by Ragnar Frisch that develops a systematic regression-based framework for analyzing interdependent economic relationships.
-
C.
The Theory of Confounding
The Theory of Confounding is a foundational chapter in R.A. Fisher’s work on experimental design that explains how to manage and interpret the mixing of treatment effects with nuisance factors in statistical experiments.
-
D.
Bayesian model averaging
Bayesian model averaging is a statistical technique that combines predictions from multiple models by weighting them according to their posterior probabilities to account for model uncertainty.
-
E.
Generalized method of moments
The generalized method of moments is an econometric estimation technique that uses sample moments to infer model parameters without requiring full specification of the underlying probability distribution.
- F. None of above. chosen
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.