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, 3rd Edition, New York: John Wiley & Sons.

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

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

Hastie, T. J., Tibshirani, R. J., and Friedman, J. H. (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. diss., University of 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, 2nd 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), “Quasi-likelihood 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.