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Confidence intervals for marginal parameters under fractional linear regression imputation for missing data

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  • Qin, Yongsong
  • Rao, J.N.K.
  • Ren, Qunshu

Abstract

Item nonresponse occurs frequently in sample surveys and other applications. Imputation is commonly used to fill in the missing item values in a random sample {Yi;i=1,...,n}. Fractional linear regression imputation, based on the model with independent zero mean errors [epsilon]i, is used to create one or more imputed values in the data file for each missing item Yi, where {Xi,i=1,...,n}, is observed completely. Asymptotic normality of the imputed estimators of the mean [mu]=E(Y), distribution function [theta]=F(y) for a given y, and qth quantile [theta]q=F-1(q),0

Suggested Citation

  • Qin, Yongsong & Rao, J.N.K. & Ren, Qunshu, 2008. "Confidence intervals for marginal parameters under fractional linear regression imputation for missing data," Journal of Multivariate Analysis, Elsevier, vol. 99(6), pages 1232-1259, July.
    • Handle: RePEc:eee:jmvana:v:99:y:2008:i:6:p:1232-1259
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    References listed on IDEAS

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    1. Jae Kwang Kim, 2004. "Fractional hot deck imputation," Biometrika, Biometrika Trust, vol. 91(3), pages 559-578, September.
    2. Qihua Wang & J. N. K. Rao, 2002. "Empirical Likelihood‐based Inference in Linear Models with Missing Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 29(3), pages 563-576, September.
    3. Qihua Wang, 2002. "Empirical likelihood-based inference in linear errors-in-covariables models with validation data," Biometrika, Biometrika Trust, vol. 89(2), pages 345-358, June.
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    Cited by:

    1. Hong-Xia Xu & Guo-Liang Fan & Han-Ying Liang, 2017. "Hypothesis test on response mean with inequality constraints under data missing when covariables are present," Statistical Papers, Springer, vol. 58(1), pages 53-75, March.

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