References
- Asparouhov, T. and Muthén, B. (2005). Multivariate statistical modeling with survey data. In The 2005 FCSM Research Conference, Washington, DC Area, 14–16.
- Atkinson, A. C. and Riani, M. (2000). Robust Diagnostic Regression Analysis. New York: Springer-Verlag.
- Atkinson, A. C. and Riani, M. (2004). The forward search and data visualization. Computational Statistics, 19(1): 29–54. doi:10.1007/BF02915275
- Belsley, D. A., Kuh, E., and Welsch, R. E. (1980). Regression Diagnostics. New York: John Wiley and Sons.
- Binder, D. A. (1983). On the variances of asymptotically normal estimators from complex surveys. International Statistical Review / Revue Internationale de Statistique, 51(3): 279–292. doi:10.2307/1402588
- Bollen, K. A., Biemer, P. P., Karr, A. F., Tueller, S., and Berzofsky, M. E. (2016). Are survey weights needed? A review of diagnostic tests in regression analysis. Annual Review of Statistics and Its Application, 3(1): 375–392. doi:10.1146/annurev-statistics-011516-012958
- Chambers, R. L. (1986). Outlier robust finite population estimation. Journal of the American Statistical Association, 81(396): 1063–1069. doi:10.1080/01621459.1986.10478374
- Chambers, R. L. and Skinner, C. J. (2003). Analysis of Survey Data. New York: Wiley.
- Cook, R. D. and Weisberg, S. (1982). Residuals and Influence in Regression. London: Chapman and Hall Ltd.
- Gelman, A. (2007). Struggles with survey weighting and regression modeling. Statistical Science, 22(2): 153–164. doi:10.1214/088342306000000691
- Lawrance, A. J. (1995). Deletion influence and masking in regression. Journal of the Royal Statistical Society, Series B, 57(1): 181–189. doi:10.1111/j.2517-6161.1995.tb02023.x
- Lee, H. (2007). Outliers in establishment surveys-they are here to stay. Paper presented at the ICES-III, June 18–21, Montreal, Quebee, Canada.
- Li, J. and Valliant, R. (2011a). Detecting groups of influential observations in linear regression using survey data—adapting the forward search method. Pakistan Journal of Statistics, 27(4): 507–528.
- Li, J. and Valliant, R. (2011b). Linear regression influence diagnostics for unclustered survey data. Journal of Official Statistics, 27(1): 99–119.
- Li, J. and Valliant, R. (2015). Linear regression diagnostics in cluster samples. Journal of Official Statistics, 71(1): 61–75. doi:10.1515/jos-2015-0003
- Pfeffermann, D. (1993). The role of sampling weights when modeling survey data. International Statistical Review / Revue Internationale de Statistique, 61(2): 317–337. doi:10.2307/1403631
- Pfeffermann, D. and Holmes, D. J. (1985). Robustness considerations in the choice of method of inference for the regression analysis of survey data. Journal of the Royal Statistical Society, A, 148(3): 268–278. doi:10.2307/2981971
- Pfeffermann, D. and Sverchkov, M. (1999). Parametric and semi-parametric estimation of regression models fitted to survey data. Sankhyā: The Indian Journal of Statistics, Series B, 61(1): 166–186.
- Pfeffermann, D. and Sverchkov, M. (2003). Analysis of Survey Data. New York: John Wiley.
- Ren, R. and Chambers, R. (2001). Studies on outlier robust estimators for finite populations. Euredit project report.
- Skinner, C. J., Holt, D., and Smith, T. M. F. (1989). Analysis of Complex Surveys. New York: Wiley.
- Weisberg, S. (2005). Applied Linear Regression. New York: John Wiley.
- Woodbury, M. A. (1950). Inverting Modified Matrices, Memorandum Report 42 Statistical Research Group. Princeton, NJ: Princeton University.