Back to Search
Start Over
On balanced random imputation in surveys
- Source :
- Biometrika. 98(2):459-471
- Publication Year :
- 2011
-
Abstract
- Random imputation methods are often used in practice because they tend to preserve the distribution of the variable being imputed, which is an important property when the goal is to estimate population quantiles. However, this type of imputation method introduces additional variability, the imputation variance, due to the random selection of residuals. In this paper, we propose a class of random balanced imputation methods under which the imputation variance is eliminated while the distribution of the variable being imputed is preserved. The rationale behind balanced imputation is to select residuals at random so that appropriate constraints are satisfied. We describe an algorithm for selecting the random residuals that can be viewed as an adaptation of the cube algorithm proposed in the context of balanced sampling (Deville & Tille, 2004). Results of a simulation study support our findings. Copyright 2011, Oxford University Press.
- Subjects :
- Statistics and Probability
Analysis of covariance
education.field_of_study
Biometrics
Statistics::Applications
Applied Mathematics
General Mathematics
Population
Sampling (statistics)
Survey sampling
Regression analysis
Agricultural and Biological Sciences (miscellaneous)
Quantitative Biology::Genomics
Statistics
Econometrics
Statistics::Methodology
Imputation (statistics)
Statistics, Probability and Uncertainty
General Agricultural and Biological Sciences
education
Mathematics
Quantile
Subjects
Details
- Volume :
- 98
- Issue :
- 2
- Database :
- OpenAIRE
- Journal :
- Biometrika
- Accession number :
- edsair.doi.dedup.....b2812670f5b1226a9ef41c5d98e1624c