References

  • Allen, D. M. (1974), “The Relationship between Variable Selection and Data Augmentation and a Method of Prediction,” Technometrics, 16, 125–127.

  • Cochran, W. G. (1977), Sampling Techniques, Third Edition, New York: John Wiley & Sons.

  • Goodnight, J. H. (1979), “A Tutorial on the Sweep Operator,” The American Statistician, 33, 149–158.

  • Harville, D. A. (1997), Matrix Algebra from a Statistician’s Perspective, New York: Springer-Verlag.

  • Hastie, T., Tibshirani, R., and Friedman, J. (2001), The Elements of Statistical Learning, New York: Springer-Verlag.

  • Jöreskog, K. G. (1973), “A General Method for Estimating a Linear Structural Equation System,” in A. S. Goldberger and O. D. Duncan, eds., Structural Equation Models in the Social Sciences, New York: Academic Press.

  • Keesling, J. W. (1972), Maximum Likelihood Approaches to Causal Analysis, Ph.D. thesis, University of Chicago, Chicago.

  • Magnus, J. R. and Neudecker, H. (1999), Matrix Differential Calculus with Applications in Statistics and Econometrics, New York: John Wiley & Sons.

  • McCullagh, P. and Nelder, J. A. (1989), Generalized Linear Models, Second Edition, London: Chapman & Hall.

  • Moore, E. H. (1920), “On the Reciprocal of the General Algebraic Matrix,” Bulletin of the American Mathematical Society, 26, 394–395.

  • Nelder, J. A. and Wedderburn, R. W. M. (1972), “Generalized Linear Models,” Journal of the Royal Statistical Society, Series A, 135, 370–384.

  • Pawitan, Y. (2001), In All Likelihood: Statistical Modelling and Inference Using Likelihood, Oxford: Clarendon Press.

  • Penrose, R. A. (1955), “A Generalized Inverse for Matrices,” Proceedings of the Cambridge Philosophical Society, 51, 406–413.

  • Pringle, R. M. and Rayner, A. A. (1971), Generalized Inverse Matrices with Applications to Statistics, New York: Hafner Publishing.

  • Särndal, C. E., Swensson, B., and Wretman, J. (1992), Model Assisted Survey Sampling, New York: Springer-Verlag.

  • Searle, S. R. (1971), Linear Models, New York: John Wiley & Sons.

  • Spearman, C. (1904), “General Intelligence Objectively Determined and Measured,” American Journal of Psychology, 15, 201–293.

  • Wedderburn, R. W. M. (1974), “Quasilikelihood Functions, Generalized Linear Models, and the Gauss-Newton Method,” Biometrika, 61, 439–447.

  • Wiley, D. E. (1973), “The Identification Problem for Structural Equation Models with Unmeasured Variables,” in A. S. Goldberger and O. D. Duncan, eds., Structural Equation Models in the Social Sciences, New York: Academic Press.