Oonsider two linear models Xi = U＇β ＋ ei, Yj = V1/2y ＋ ηj with response variables missing at random. In this paper, we assume that X, Y are missing at random （MAR） and use the inverse probability weighted imput...Oonsider two linear models Xi = U＇β ＋ ei, Yj = V1/2y ＋ ηj with response variables missing at random. In this paper, we assume that X, Y are missing at random （MAR） and use the inverse probability weighted imputation to produce ＇complete＇ data sets for X and Y. Based on these data sets, we construct an empirical likelihood （EL） statistic for the difference of X and Y （denoted as A）, and show that the EL statistic has the limiting distribution of X~, which is used to construct a confidence interval for A. Results of a simulation study on the finite sample performance of EL-based confidence intervals on A are reported.展开更多
基金Supported by the National Natural Science Foundation of China(No.11271088,11361011,11201088)Natural Science Foundation of Guangxi(No.2013GXNSFAA(019004 and 019007),2013GXNSFBA019001)
文摘Oonsider two linear models Xi = U＇β ＋ ei, Yj = V1/2y ＋ ηj with response variables missing at random. In this paper, we assume that X, Y are missing at random （MAR） and use the inverse probability weighted imputation to produce ＇complete＇ data sets for X and Y. Based on these data sets, we construct an empirical likelihood （EL） statistic for the difference of X and Y （denoted as A）, and show that the EL statistic has the limiting distribution of X~, which is used to construct a confidence interval for A. Results of a simulation study on the finite sample performance of EL-based confidence intervals on A are reported.
