References
- Burdick, R. K., & Sielken Jr., R. L. (1979). Variance estimation based on a superpopulation model in two-stage sampling. Journal of the American Statistical Association, 74, 438–440. [Taylor & Francis Online], [Web of Science ®], [Google Scholar]
- Burt, V., & Cohen, S. B. (1984). A comparison of methods to approximate standard errors for complex survey data. Review of Public Data Use, 12, 159–168. [Google Scholar]
- Cohen, S. B. (1979). An assessment of curve smoothing strategies which yield variance estimates from complex survey. Proceedings of the Survey Research Methods Section of the American Statistical Association, Washington, DC. [Google Scholar]
- Cook, D. G., & Pocock, S. J. (1983). Multiple regression in geo-graphical mortality studies with allowance for spatially correlated errors. Biometrics, 39, 361–371. doi: 10.2307/2531009 [Crossref], [Web of Science ®], [Google Scholar]
- Johnson, E. G., & King, B. F. (1987). Generalized variance functions for a complex sample survey. Journal of Official Statistics, 3, 235–250. [Google Scholar]
- Lohr, S. (2010). Sampling: Design and analysis (2nd ed.). Boston, MA: Cengage Learning. [Google Scholar]
- Rao, J. N. K. (1988). Variance estimation in sample surveys. In P. R. Krishnaiah & C. R. Rao (Eds.), Handbook of statistics (Vol. 6, pp. 427–447). Amsterdam: Elsevier Science Publishers B.V. [Crossref], [Google Scholar]
- Rao, J. N. K., & Wu, C. F. J. (1988). Resampling inference with complex survey data. Journal of the American Statistical Association, 83, 231–241. doi: 10.1080/01621459.1988.10478591 [Taylor & Francis Online], [Web of Science ®], [Google Scholar]
- Royall, R. M. (1976). The linear least squares prediction approach to two-stage sampling. Journal of the American Statistical Association, 71, 657–664. doi: 10.1080/01621459.1976.10481542 [Taylor & Francis Online], [Web of Science ®], [Google Scholar]
- Royall, R. M. (1986). The prediction approach to robust variance estimation in two-stage cluster sampling. Journal of the American Statistical Association, 81, 119–123. doi: 10.1080/01621459.1986.10478247 [Taylor & Francis Online], [Web of Science ®], [Google Scholar]
- Scott, A. J., & Smith, T. M. F. (1969). Estimation in multi-stage surveys. Journal of the American Statistical Association, 64, 830–840. doi: 10.1080/01621459.1969.10501015 [Taylor & Francis Online], [Web of Science ®], [Google Scholar]
- Shook-Sa, B., Heller, D., Williams, R., Couzens, G. L., & Berzofsky, M. (2013). Comparing generalized variance functions to direct variance estimation for the national crime victimization survey. 2013 research conference, Federal Committee on Statistical Methodology (FCSM), Washington, DC. [Google Scholar]
- Thompson, M. E. (2015). Using longitudinal complex survey data. The Annual Review of Statistics and Its Application, 2, 305–320. doi: 10.1146/annurev-statistics-010814-020403 [Crossref], [Web of Science ®], [Google Scholar]
- U.S. Census Bureau. (2006). Current population survey: Design and methodology (Technical Paper 66). [Google Scholar]
- U.S. Census Bureau. (2009). Estimating ASEC variances with replicate weights. Part 1: Instructions for using the ASEC public use replicate weight file to create ASEC variance estimates. [Google Scholar]
- Valliant, R. L. (1987). Generalized variance functions in stratified two-stage sampling. Journal of the American Statistical Association, 82, 499–508. doi: 10.1080/01621459.1987.10478454 [Taylor & Francis Online], [Web of Science ®], [Google Scholar]
- Wolter, K. M. (2007). Introduction to variance estimation (2nd ed.). New York, NY: Spring-Verlag. [Google Scholar]