z-logo
Premium
Imputation for missing values and corresponding variance estimation
Author(s) -
Sitter R. R.,
Rao J. N. K.
Publication year - 1997
Publication title -
canadian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.804
H-Index - 51
eISSN - 1708-945X
pISSN - 0319-5724
DOI - 10.2307/3315353
Subject(s) - imputation (statistics) , missing data , statistics , variance (accounting) , mathematics , estimation , econometrics , computer science , economics , accounting , management
Imputation is commonly used to compensate for missing data in surveys. We consider the general case where the responses on either the variable of interest y or the auxiliary variable x or both may be missing. We use ratio imputation for y when the associated x is observed and different imputations when x is not observed. We obtain design‐consistent linearization and jackknife variance estimators under uniform response. We also report the results of a simulation study on the efficiencies of imputed estimators, and relative biases and efficiencies of associated variance estimators.

This content is not available in your region!

Continue researching here.

Having issues? You can contact us here