Accounting for not‐at‐random missingness through imputation stacking
Author:
Affiliation:
1. Department of Biostatistics University of Michigan Ann Arbor Michigan USA
Publisher
Wiley
Subject
Statistics and Probability,Epidemiology
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1002/sim.9174
Reference21 articles.
1. Multiple Imputation for Nonresponse in Surveys
2. A multivariate technique for multiply imputing missing values using a sequence of regression models;Raghunathan TE;Surv Methodol,2001
3. Fully conditional specification in multivariate imputation
4. Statistical Analysis with Missing Data
5. On the use of the not-at-random fully conditional specification (NARFCS) procedure in practice
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