Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
권호 표지
DOI QR코드

DOI QR Code

Propensity Score Weighting Adjustment for Internet Surveys for Korean Presidential Election

인터넷 선거여론조사 가중치보정을 위한 성향점수의 활용

  • Kim, Young-Won (Department of Statistics, Sookmyung Women's University) ;
  • Be, Ye-Young (Department of Statistics, Sookmyung Women's University)
  • 김영원 (숙명여자대학교 수학통계학부) ;
  • 배예영 (숙명여자대학교 수학통계학부)
  • Published : 2010.01.31
Download PDF
⟨ Previous Next ⟩

Abstract

Propensity score adjustment(PSA) has been suggested as approach to adjustment for volunteer internet survey. PSA attempts to decrease the biases arising from noncoverage and nonprobability sampling in volunteer panel internet surveys. Although PSA is an appealing method, its application for internet survey regarding Korea presidential election and its effectiveness is not well investigated. In this study, we compare the Ni Korea internet survey with the telephone survey conducted by MBMR and KBS for 2007 Korean presidential election. The result of study show that the accuracy of internet survey can be improved by using PSA. And it is critical to include covariates that highly related to the voting tendency and the role of nondemographic variables seems important to improving PSA for Korea presidential election prediction.

본 연구에서는 2007년에 실시한 17대 대통령 선거를 위한 NI Korea의 인터넷 패널조사와 KBS의 대선 패널 전화여론조사 결과를 토대로 인터넷조사와 전화조사의 차이를 비교하고, 인터넷조사의 활용 가능성을 검토해 보고자 한다. 인터넷조사는 조사대상자가 인터넷 사용자로 제한됨에 따라 발생하는 포함오차와 조사 참여 의사를 갖는 사람들만을 조사에 참여시킴으로써 발생하는 선택편향 등으로 인해 흔히 표본의 대표성이 문제점으로 지적되고 있다. 이런 문제점을 해결하기 위해 인터넷 사용자 표본이 전체 유권자 표본을 설명 할 수 있도록 성향점수(Propensity score)를 사용하여 가중치를 보정하는 방안을 제시한다. 17대 대선 자료를 기초로 한 사례분석을 통해, 적절한 성향점수보정 기법을 적용하는 경우 인터넷조사를 선거예측에 활용하는것이 가능하다는 결론을 얻을 수 있었다.

Keywords

References

  1. 김원용, 이홍철 (2003). 웹조사의 모집단대표성 확보를 위한 성향가중 모형의 적합성 검증, <방송연구>, 여름호, 143-166.
  2. Cochran, W. G. (1968). The effectiveness of adjustment by subclassification in removing bias in observational studies, Biometrics, 24, 295-313. https://doi.org/10.2307/2528036
  3. D'Agostino, R. B. Jr. (1998). Propensity score methods for bias reduction for the comparison of a treatment to a non-randomized control group, Statistics in Medicine, 17, 2265-2281. https://doi.org/10.1002/(SICI)1097-0258(19981015)17:19<2265::AID-SIM918>3.0.CO;2-B
  4. Duncan, K. B. and Stasny, E. A. (2001). Using propensity scores to control coverage bias in telephone surveys, Survey Methodology, 27, 121-130.
  5. Lee, S. (2006). Propensity score adjustment as a weighting scheme for volunteer panel web surveys, Journal of Official Statistics.
  6. Rosenbaum, P. R. and Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects, Biometrika, 70, 41-55. https://doi.org/10.1093/biomet/70.1.41
  7. Rosenbaum, P. R. and Rubin, D. B. (1984). Recucing bias in observational studies. Using subclassification on the propensity score, Journal of the American Statisical Association, 79, 516-524. https://doi.org/10.2307/2288398
  8. Smith, P. J., Rao, J. N. K., Battaglia, M. P., Daniels, D. and Ezzati-Rice, T. (2000). Compensating for nonresponse bias in the national immunization survey using response propensities, In Proceedings of the American Statistical Association, Section on Survey Research Methods, 641-646.
  9. Taylor, H. (2000). Dose internet research Work- Comparing online survey result with telephone survey, International Journal of Market Research, 42, 58-63.
  10. Taylor, H., Bremer, J., Overmeyer, C., Siegel, J. W. and Terhanian, G. (2001). The record of internet-based opinion polls in predicting the results of 72 races in the November 2000 US Elections, International Journal of Market Research, 43, 127-135.
  11. Vartivarian, S. and Little, R. (2003). On the formation of weighting adjustment cells for unit nonresponse, University of Michigan Department of Biostatistics Working Paper Series.
  12. Vehovar, V. and Manfreda, K. L. (1999). Web surveys: Can the weighting solve the problem- Proceedings of American Statistical Association, Section on Survey Research Methods, 962-967.