Variance Estimation of Imputed Estimator In Complex Design

• 발행기관: 한국자료분석학회
• 저자명: 김수택(Soo-Taek Kim)
• 간행물 정보: 『Journal of The Korean Data Analysis Society (JKDAS)』Vol.8 No.6, 2157~2172쪽, 전체 16쪽
• 주제분류: 자연과학 > 통계학
• 파일형태: PDF
• 발행일자: 2006.12.30

영문 초록

We have studied imputation and variance estimation method under the regression imputation model. We proposed the best linear unbiased predicted value as an imputed value under the model, and obtained unbiased variance estimator of the imputed sample mean. Basically, our method is an extension of Sarndal s(1992) model based approach to general regression model. Through a simulation study, we confirmed that the sample mean after the prediction imputation is nearly unbiased under nonignorable as well as ignorable response mechanism and the proposed variance estimator is more efficient than other known adjusted variance estimators. Furthermore, the proposed variance estimator is applicable regardless of ignorable or nonignorable response mechanism.

목차

1. Introduction

2. Variance Estimation under Imputation Model

3. Variance Estimation Under Prediction Imputation

4. A Simulation Study

5. Concluding Remarks

References

키워드

Prediction imputation Regression imputation ignorable nonignorable response mechanism Variance estimation under imputation