Prediction of Exit Polls for the Presidential Election in 2007 and 2013 by Using Nonresponse Models

• 발행기관: 한국자료분석학회
• 저자명: Boseung Choi Seongyong Kim
• 간행물 정보: 『Journal of The Korean Data Analysis Society (JKDAS)』Vol.19 No.1, 1~9쪽, 전체 9쪽
• 주제분류: 자연과학 > 통계학
• 파일형태: PDF
• 발행일자: 2017.02.28

영문 초록

Estimation of nonresponses in exit polls frequently produces inaccurate election results. Since estimates of nonresponses differ depending on the assumed mechanism, nonresponse mechanism should be determined prior to the analysis. However, nonresponse mechanism is not testable. From this problem, estimates from all possible models need to be provided. Along with the selection of nonresponse mechanism, ML (maximum likelihood) estimates under NMAR (not missing at random) have a boundary solution problem which is that cell expectations of more than one columns are estimated as zeros. To overcome the boundary solution problem, various Bayesian models have been suggested. In this paper, ML estimation under MAR (missing at random) and NMAR as well as Bayesian estimation under NMAR are applied to the two exit polls for 2007 and 2013 Korean presidential elections with 53 contingency tables. In comparing ML and Bayesian estimates, we also consider weighting methods to reduce biases. As results, ML estimates under MAR produce more accurate election results and better than the Bayesian approaches under NMAR.

목차

1. Introduction

2. Presidential election forecasts

3. ML, Bayesian estimates and weighting methods

4. Application to the 2007 and 2013 Korean presidential elections

5. Conclusion

키워드

contingency table nonresponse mechanism boundary solution exit poll