• Bollen, K. A. and Jackman, R. (1990). Regression diagnostics: an expository treatment of outliers and influential cases. In: Fox, J. and Scott Long, J. (Eds.), Modern Methods of Data Analysis. Sage, Newbury Park, CA, pp. 257291.
  • Broman, K. W., Wu, H., Sen, Ś., and Churchill, G. A. (2003). R/qtl: QTL mapping in experimental crosses. Bioinformatics 19, 889890.
  • Churchill, G. A. and Doerge, R. W. (1994). Empirical threshold values for quantitative trait mapping. Genetics 138, 963971.
  • Cook, D. (1977). Detection of influential observation in linear regression. Technometrics 19, 1518.
  • Cook, D. (1986). Assessment of local influence. Journal of the Royal Statistical Society, Series B 2, 133169.
  • Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters 27, 861874.
  • Hampel, F. R., Ronchetti, E. M., Rousseeuw, P. J., and Stahel, W. A. (1986). Robust Statistics: The Approach Based on Influence Functions. Wiley, New York, NY.
  • Hayat, Y., Yang, J., Xu, H.-M., and Zhu, J. (2008). Influence of outliers on QTL mapping for complex traits. Journal of Zhejiang University, Science B 9, 931937.
  • Kao, C.-H. and Zeng, Z.-B. (1997). General formulas for obtaining the MLEs and the asymptotic variance-covariance matrix in mapping quantitative trait loci when using the EM algorithm. Biometrics 53, 653665.
  • Kao, C.-H., Zeng, Z.-B., and Teasdale, R. D. (1999). Multiple interval mapping for quantitative trait loci. Genetics 152, 12031216.
  • Lander, E. S. and Botstein, D. (1989). Mapping Mendelian factors underlying quantitative traits using RFLP linkage maps. Genetics 121, 185199.
  • Lu, J., Ko, D., and Chang, T. (1997). The standardized influence matrix and its applications. Journal of the American Statistical Association 92, 15721580.
  • Manly, K. F. and Olson, J. M. (1999). Overview of QTL mapping software and introduction to Map Manager QT. Mammalian Genome 10, 327334.
  • Murphy, A. A. and van der Vaart, A. A. (2000). On profile likelihood. Journal of the American Statistical Association 95, 449465.
  • Sen, Ś. and Churchill, G. (2001). A statistical framework for quantitative trait mapping. Genetics 159, 371387.
  • Siegmund, D. and Yakir, B. (2007). The Statistics of Gene Mapping, Springer, New York, NY.
  • Takada, T., Mita, A., Maeno, A., Sakai, T., Shitara, H., Kikkawa, Y., Moriwaki, K., Yonekawa, H., and Shiroishi, T. (2008). Mouse inter-subspecific consomic strains for genetic dissection of quantitative complex traits. Genome Research 18, 500508. NIG Mouse phenotype database
  • Tanaka, Y. (1994). Recent advance in sensitivity analysis in multivariate statistical methods. Journal of the Japanese Society of Computational Statistics 7, 125.
  • White, H. (1996). Estimation, Inference and Specification Analysis. Cambridge University Press, Cambridge, UK.
  • Wright, F. A. and Kong, A. (1997). Linkage mapping in experimental crosses: the robustness of single gene models. Genetics 146, 417425.
  • Wu, R., Ma, C.-X., and Casella, G. (2007). Statistical Genetics of Quantitative Traits: Linkage, Maps and QTL. Springer, New York, NY.
  • Zeng, Z.-B. (1993). Theoretical basis for separation of multiple linked gene effects in mapping quantitative trait loci. Proceedings of the National Academy of Sciences USA 90, 1097210976.
  • Zewotir, T. and Galpin, J. S. (2005). Influence diagnostics for linear mixed models. Journal of Data Science 3, 153177.