Statistical Analysis with Missing Data¶
Little, R., & Rubin, D. (2019). Statistical Analysis with Missing Data. Wiley.
Cited by¶
2 citations across 2 artifacts.
Each citation links to the sentence it supports in the citing article.
Primes¶
- Imputation
- Statistics and data science. The canonical case — multiple imputation, expectation-maximization, k-nearest-neighbor, regression, and chained-equation methods, under the formal missing-data-mechanism frame.
This sourceStandard reference on missing-data methods (EM, multiple imputation, chained equations), implicit-imputation hazards of complete-case and mean substitution, and cross-domain transfer of the discipline.
- Statistics and data science. The canonical case — multiple imputation, expectation-maximization, k-nearest-neighbor, regression, and chained-equation methods, under the formal missing-data-mechanism frame.
- Missing Data Mechanisms (MCAR, MAR, MNAR)
- Complete-case analysis produces unbiased estimates (though inefficient)
This sourceLittle-Rubin comprehensive missing-data analysis covering complete-case analysis under MCAR.
- Complete-case analysis produces unbiased estimates (though inefficient)
Verification¶
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Registry ID ref:2be1482b082f · see in the full table