H. Liang, S. J. Wang, J. M. Robbins and R. J. Carroll, “Estimation in Partially Linear Models with Missing Covariates,” Journal of the American Statistical Association, Vol. 99, No. 466, 2004, pp. 357-367. doi：10.1198/016214504000000421

has been cited by the following article:

• TITLE: Imputed Empirical Likelihood for Varying Coefficient Models with Missing Covariates

  AUTHORS: Peixin Zhao

  KEYWORDS: Empirical Likelihood; Varying Coefficient Model; Missing Covariate

  JOURNAL NAME: Open Journal of Applied Sciences, Vol.3 No.1B1, July 11, 2013

  ABSTRACT: The empirical likelihood-based inference for varying coefficient models with missing covariates is investigated. An imputed empirical likelihood ratio function for the coefficient functions is proposed, and it is shown that iis limiting distribution is standard chi-squared. Then the corresponding confidence intervals for the regression coefficients are constructed. Some simulations show that the proposed procedure can attenuate the effect of the missing data, and performs well for the finite sample.