A0502
Title: Sample-split regression estimation with high dimensional covariates in survey sampling
Authors: Yonghyun Kwon - Korea Military Academy (Korea, South) [presenting]
Jae Kwang Kim - Iowa State University (United States)
Shu Yang - North Carolina State University (United States)
Abstract: In a finite population sampling survey, model-assisted regression estimation is developed to incorporate the auxiliary information efficiently. When there are high-dimensional auxiliary data sets, adding too many auxiliary variables may increase the estimation error and lead to biased estimation. Particularly under informative sampling, the bias of the high dimensional regression estimator may not be negligible. A novel application of the sample-split estimation method is presented for regression estimation under informative sampling. The proposed method is shown to be consistent even when the auxiliary variables are high-dimensional, and the sampling design is informative. Variance estimation for the sample-split estimator is discussed. Results from a limited simulation study are also presented.
