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Original Articles

Multiple cases deletion measures in linear measurement error models

Pages 954-963 | Received 27 Jun 2017, Accepted 20 Dec 2017, Published online: 17 Jan 2018

References

  • Barrett, B. E., and R. F. Ling. 1992. General classes of influence measures for multivariate regression. Journal of the American Statistical Association 87:184–91. doi:10.1080/01621459.1992.10475191.
  • Belsley, D. A., E. Kuh, and R. E. Welsch. 1980. Regression diagnostics: identifying influential data and sources of collinearity. New York: Wiley.
  • Chatterjee, S., and A. S. Hadi. 1986. Influential observations, high leverage points and outliers in linear regression (with discussion). Statistical Science 1:379–416. doi:10.1214/ss/1177013622.
  • Cook, R. D. 1977. Detection of influential observations in linear regression. Technometrics 19:15–18.
  • Cook, R. D., and S. Weisberg. 1982. Residuals and influence in regression. London: Chapman and Hall.
  • Fuller, W. A. 1987. Measurement error models. New York: Wiley.
  • Gimenz, P., and H. Bolfarine. 1997. Corrected score functions in classical error-in-variables and incidental parameter models. Austral. J. Statist. 39:325–44.
  • Gray, B. J., and R. F. Ling. 1984. K-clustering as a detection tool for influential subsets in regression. Technometrics 26:305–18.
  • Hadi, A. S. 1992. A new measure of overall potential influence in linear regression. Computational Statistics and Data Analysis 14:1–27. doi:10.1016/0167-9473(92)90078-T.
  • Hanfelt, J. J., and K. Y. Liang. 1997. Approximate likelihood for generalized linear errors-in-variables models. J. Roy. Statist. Soc. Ser. B 59:627–37.
  • Haslett, J. 1999. A simple derivation of deletion diagnostic results for the general linear model with correlated errors. Journal of the Royal Statistical Society, Series B 61:603–09. doi:10.1111/1467-9868.00195.
  • Kelly, G. E. 1984. The influence function in the errors in variables problems. Annals of Statistics 12:87–100. doi:10.1214/aos/1176346394.
  • Lu, J., D. Ko, and T. Chang. 1997. The standardized influence matrix and its applications. Journal of the American Statistical Association 92:1572–80. doi:10.1080/01621459.1997.10473679.
  • Nakamura, T. 1990. Corrected score function for errors-in-variables models: Methodology and application to generalized linear models. Biometrika 77:127–37. doi:10.1093/biomet/77.1.127.
  • Nakamura, T. 1992. Proportional hazards model with covariates subject to measurement error. Biometrics 48:829–38. doi:10.2307/2532348.
  • Pena, D., and V. J. Yohai. 1995. The detection of influential subsets in linear regression by using an influence matrix. Journal of the Royal Statistical Society. Series B 57:145–56.
  • Wang, D. Q., and F. Critchley. 2000. Multiple deletion measures and influence in regression model. Communication in Statistics: Theory and Methods 29(11):2391–404. doi:10.1080/03610920008832612.
  • Wellman, J. M., and R. F. Gunst. 1991. Influence diagnostics for linear measurement errors models. Biometrika 78:373–80. doi:10.1093/biomet/78.2.373.
  • Welsch, R. E. 1982. Influence functions and regression diagnostics. In Modern data analysis, eds. R. L. Launer and A. F. Siegel, New York: Academic.
  • Zhong, X. P., B. C. Wei, and W. K. Fung. 2000. Influence analysis for linear measurement error models. Annals of the Institute of Statistical Mathematics 52:367–79. doi:10.1023/A:1004126108349.

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