Browse > Article
http://dx.doi.org/10.5351/CKSS.2010.17.1.055

Propensity Score Weighting Adjustment for Internet Surveys for Korean Presidential Election  

Kim, Young-Won (Department of Statistics, Sookmyung Women's University)
Be, Ye-Young (Department of Statistics, Sookmyung Women's University)
Publication Information
Communications for Statistical Applications and Methods / v.17, no.1, 2010 , pp. 55-66 More about this Journal
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.
Keywords
Internet survey; presidential election survey; propensity score adjustment(PSA); weight;
Citations & Related Records
연도 인용수 순위
  • Reference
1 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.
2 Taylor, H. (2000). Dose internet research Work- Comparing online survey result with telephone survey, International Journal of Market Research, 42, 58-63.
3 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.
4 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.
5 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.
6 Duncan, K. B. and Stasny, E. A. (2001). Using propensity scores to control coverage bias in telephone surveys, Survey Methodology, 27, 121-130.
7 김원용, 이홍철 (2003). 웹조사의 모집단대표성 확보를 위한 성향가중 모형의 적합성 검증, <방송연구>, 여름호, 143-166.
8 Cochran, W. G. (1968). The effectiveness of adjustment by subclassification in removing bias in observational studies, Biometrics, 24, 295-313.   DOI   ScienceOn
9 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.   DOI   ScienceOn
10 Lee, S. (2006). Propensity score adjustment as a weighting scheme for volunteer panel web surveys, Journal of Official Statistics.
11 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.   DOI   ScienceOn
12 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.   DOI