References - S

A B C D E F G H I J K L M N O P Q R S T U V W Y Z

Sandler, G. H. (1963). System reliability engineering. Englewood Cliffs, NJ: Prentice-Hall.

Satorra, A., & Saris, W. E. (1985). Power of the likelihood ratio test in covariance structure analysis. Psychometrika, 50, 83-90.

Saxena, K. M. L., & Alam, K. (1982). Estimation of the noncentrality parameter of a chi squared distribution. Annals of Statistics, 10, 1012-1016.

Scheffé, H. (1953). A method for judging all possible contrasts in the analysis of variance. Biometrika, 40, 87-104.

Scheffé, H. (1959). The analysis of variance. New York: Wiley.

Scheffé, H. (1963). The simplex-centroid design for experiments with mixtures. Journal of the Royal Statistical Society, B25, 235-263.

Scheffé, H., & Tukey, J. W. (1944). A formula for sample sizes for population tolerance limits. Annals of Mathematical Statistics, 15, 217.

Scheines, R. (1994). Causation, indistinguishability, and regression. In F. Faulbaum, (Ed.), SoftStat '93. Advances in statistical software 4. Stuttgart: Gustav Fischer Verlag.

Schiffman, S. S., Reynolds, M. L., & Young, F. W. (1981). Introduction to multidimensional scaling: Theory, methods, and applications. New York: Academic Press.

Schimek, M. G. (2000). Smoothing and regression: Approaches, computations, and application. New York: Wiley.

Schmidt, F. L., & Hunter, J. E. (1997). Eight common but false objections to the discontinuation of significance testing in the analysis of research data. In Harlow, L. L., Mulaik, S. A., & Steiger, J. H. (Eds.), What if there were no significance tests. Mahwah, NJ: Lawrence Erlbaum Associates.

Schmidt, P., & Muller, E. N. (1978). The problem of multicollinearity in a multistage causal alienation model: A comparison of ordinary least squares, maximum-likelihood and ridge estimators. Quality and Quantity, 12, 267-297.

Schmidt, P., & Sickles, R. (1975). On the efficiency of the Almon lag technique. International Economic Review, 16, 792-795.

Schmidt, P., & Waud, R. N. (1973). The Almon lag technique and the monetary versus fiscal policy debate. Journal of the American Statistical Association, 68, 11-19.

Schnabel, R. B., Koontz, J. E., and Weiss, B. E. (1985). A modular system of algorithms for unconstrained minimization. ACM Transactions on Mathematical Software, 11, 419-440.

Schneider, H. (1986). Truncated and censored samples from normal distributions. New York: Marcel Dekker.

Schneider, H., & Barker, G.P. (1973). Matrices and linear algebra (2nd ed.). New York: Dover Publications.

Schönemann, P. H., & Steiger, J. H. (1976). Regression component analysis. British Journal of Mathematical and Statistical Psychology, 29, 175-189.

Schrock, E. M. (1957). Quality control and statistical methods. New York: Reinhold Publishing.

Schwarz, G. ( 1978). Estimating the dimension of a model. Annals of Statistics, 6, 461-464.

Scott, D. W. (1979). On optimal and data-based histograms. Biometrika, 66, 605-610.

Scott M. Kowalski and Kevin J. Potcner, Quality Progress, November 2003

Searle, S. R. (1987). Linear models for unbalanced data. New York: Wiley.

Searle, S. R., Casella, G., & McCulloch, C. E. (1992). Variance components. New York: Wiley.

Searle, S., R., Speed., F., M., & Milliken, G. A. (1980). The population marginal means in the linear model: An alternative to least squares means. The American Statistician, 34, 216-221.

Seber, G. A. F., & Wild, C. J. (1989). Nonlinear regression. New York: Wiley.

Sebestyen, G. S. (1962). Decision making processes in pattern recognition. New York: Macmillan.

Seder, L. A. (1962). Quality improvement. In J. M. Juran. Quality control  handbook. New York: McGraw-Hill.

Sen, P. K., & Puri, M. L. (1968). On a class of multivariate multisample rank order tests, II: Test for homogeneity of dispersion matrices. Sankhya, 30, 1-22.

Serlin, R. A., & Lapsley, D. K. (1993). Rational appraisal of psychological research and the good-enough principle. In G. Keren & C. Lewis (Eds.), A handbook for data analysis in the behavioral sciences: Methodological issues (pp. 199-228). Hillsdale, NJ: Lawrence Erlbaum Associates.

Serlin. R. A., & Lapsley, D. K. (1985). Rationality in psychological research: The good-enough principle. American Psychologist, 40, 7383.

Shapiro, A., & Browne, M. W. (1983). On the investigation of local identifiability: A counter example. Psychometrika, 48, 303-304.

Shapiro, S. S., Wilk, M. B., & Chen, H. J. (1968). A comparative study of various tests of normality. Journal of the American Statistical Association, 63, 1343-1372.

Shepherd, A. J. (1997). Second-Order Methods for Neural Networks. New York: Springer.

Sheskin, D. J. (1997), Handbook of Parametric and Nonparametric Statistical Procedures, Boca Raton, FL: CRC Press.

Shewhart, W. A. (1931). Economic control of quality of manufactured product. New York: D. Van Nostrand.

Shewhart, W. A. (1939). Statistical method from the viewpoint of quality. Washington, DC: The Graduate School Department of Agriculture.

Shirland, L. E. (1993). Statistical quality control with microcomputer applications. New York: Wiley.

Shiskin, J., Young, A. H., & Musgrave, J. C. (1967). The X-11 variant of the census method II seasonal adjustment program. (Technical paper no. 15). Bureau of the Census.

Shumway, R. H. (1988). Applied statistical time series analysis. Englewood Cliffs, NJ: Prentice Hall.

Siddiqi, N. (2006). Credit risk scorecards: Developing and implementing intelligent credit scoring. Wiley & Sons, NY.

Siegel, A. E. (1956). Film-mediated fantasy aggression and strength of aggressive drive. Child Development, 27, 365-378.

Siegel, S. (1956). Nonparametric statistics for the behavioral sciences. New York: McGraw-Hill.

Siegel, S., & Castellan, N. J. (1988). Nonparametric statistics for the behavioral sciences (2nd ed.) New York: McGraw-Hill.

Silverman, B. W. (1986). Density Estimation for Statistics and Data Analysis. Chapman and Hall, London

Simkin, D., & Hastie, R. (1986). Towards an information processing view of graph perception. Proceedings of the Section on Statistical Graphics, American Statistical Association, 11-20.

Sinha, S. K., & Kale, B. K. (1980). Life testing and reliability estimation. New York: Halstead.

Smirnov, N. V. (1948). Table for estimating the goodness of fit of empirical distributions. Annals of Mathematical Statistics, 19, 279-281.

Smith, D. J. (1972). Reliability engineering. New York: Barnes & Noble.

Smith, K. (1953). Distribution-free statistical methods and the concept of power efficiency. In L. Festinger and D. Katz (Eds.), Research methods in the behavioral sciences (pp. 536-577). New York: Dryden.

Sneath, P. H. A., & Sokal, R. R. (1973). Numerical taxonomy. San Francisco: W. H. Freeman & Co.

Snee, R. D. (1975). Experimental designs for quadratic models in constrained mixture spaces. Technometrics, 17, 149-159.

Snee, R. D. (1979). Experimental designs for mixture systems with multi-component constraints. Communications in Statistics - Theory and Methods, A8(4), 303-326.

Snee, R. D. (1985). Computer-aided design of experiments - some practical experiences. Journal of Quality Technology, 17, 222-236.

Snee, R. D. (1986). An alternative approach to fitting models when re-expression of the response is useful. Journal of Quality Technology, 18, 211-225.

Sokal, R. R., & Mitchener, C. D. (1958). A statistical method for evaluating systematic relationships. University of Kansas Science Bulletin, 38, 1409.

Sokal, R. R., & Sneath, P. H. A. (1963). Principles of numerical taxonomy. San Francisco: W. H. Freeman & Co.

Soper, H. E. (1914). Tables of Poisson's exponential binomial limit. Biometrika, 10, 25-35.

Spearman, C. (1904). "General intelligence," objectively determined and measured. American Journal of Psychology, 15, 201-293.

Speckt, D.F. (1990). Probabilistic Neural Networks. Neural Networks 3 (1), 109-118.

Speckt, D.F. (1991). A Generalized Regression Neural Network. IEEE Transactions on Neural Networks 2 (6), 568-576.

Spirtes, P., Glymour, C., & Scheines, R. (1993). Causation, prediction, and search. Lecture Notes in Statistics, V. 81. New York: Springer-Verlag.

Spjotvoll, E., & Stoline, M. R. (1973). An extension of the T-method of multiple comparison to include the cases with unequal sample sizes. Journal of the American Statistical Association, 68, 976-978.

Springer, M. D. (1979). The algebra of random variables. New York: Wiley.

Spruill, M. C. (1986). Computation of the maximum likelihood estimate of a noncentrality parameter. Journal of Multivariate Analysis, 18, 216-224.

Stefansky, W. (1972). Rejecting Outliers in Factorial Designs. Technometrics, 14, 469-479

Steiger, J. H. (1979). Factor indeterminacy in the 1930's and in the 1970's; some interesting parallels. Psychometrika, 44, 157-167.

Steiger, J. H. (1980a). Tests for comparing elements of a correlation matrix. Psychological Bulletin, 87, 245-251.

Steiger, J. H. (1980b). Testing pattern hypotheses on correlation matrices: Alternative statistics and some empirical results. Multivariate Behavioral Research, 15, 335-352.

Steiger, J. H. (1988). Aspects of person-machine communication in structural modeling of correlations and covariances. Multivariate Behavioral Research, 23, 281-290.

Steiger, J. H. (1989). EzPATH: A supplementary module for SYSTAT and SYGRAPH. Evanston, IL: SYSTAT, Inc.

Steiger, J. H. (1990). Some additional thoughts on components and factors. Multivariate Behavioral Research, 25, 41-45.

Steiger, J. H., & Browne, M. W. (1984). The comparison of interdependent correlations between optimal linear composites. Psychometrika, 49, 11-24.

Steiger, J. H., & Fouladi, R. T. (1992). R2: A computer program for interval estimation, power calculation, and hypothesis testing for the squared multiple correlation. Behavior Research Methods, Instruments, and Computers, 4, 581582.

Steiger, J. H., & Fouladi, R. T. (1997). Noncentrality interval estimation and the evaluation of statistical models. In Harlow, L. L., Mulaik, S. A., & Steiger, J. H. (Eds.), What if there were no significance tests. Mahwah, NJ: Lawrence Erlbaum Associates.

Steiger, J. H., & Hakstian, A. R. (1982). The asymptotic distribution of elements of a correlation matrix: Theory and application. British Journal of Mathematical and Statistical Psychology, 35, 208-215.

Steiger, J. H., & Lind, J. C. (1980). Statistically-based tests for the number of common factors. Paper presented at the annual Spring Meeting of the Psychometric Society in Iowa City. May 30, 1980.

Steiger, J. H., & Schönemann, P. H. (1978). A history of factor indeterminacy. In S. Shye, (Ed.), Theory Construction and Data Analysis in the Social Sciences. San Francisco: Jossey-Bass.

Steiger, J. H., Shapiro, A., & Browne, M. W. (1985). On the multivariate asymptotic distribution of sequential chi-square statistics. Psychometrika, 50, 253-264.

Stelzl, I. (1986). Changing causal relationships without changing the fit: Some rules for generating equivalent LISREL models. Multivariate Behavioral Research, 21, 309-331.

Stenger, F. (1973). Integration formula based on the trapezoid formula. Journal of the Institute of Mathematics and Applications, 12, 103-114.

Stevens, J. (1986). Applied multivariate statistics for the social sciences. Hillsdale, NJ: Erlbaum.

Stevens, W. L. (1939). Distribution of groups in a sequence of alternatives. Annals of Eugenics, 9, 10-17.

Stewart, D. K., & Love, W. A. (1968). A general canonical correlation index. Psychological Bulletin, 70, 160-163.

Steyer, R. (1992). Theorie causale regressionsmodelle [Theory of causal regression models]. Stuttgart: Gustav Fischer Verlag.

Steyer, R. (1994). Principles of causal modeling: a summary of its mathematical foundations and practical steps. In F. Faulbaum, (Ed.), SoftStat '93. Advances in statistical software 4. Stuttgart: Gustav Fischer Verlag.

Stone, M., & Brooks, R. J. (1990). Continuum Regression: Cross-validated Sequentially Constructed Prediction Embracing Ordinary Least Squares, Partial Least Squares, and Principal Components Regression, Journal of Royal Statistical Society, 52, No. 2, 237-269.

Storey, JD. (2002) A direct approach to false discovery rates. Journal of the Royal Statistical Society, Series B, 64: 479-498.

Student (1908). The probable error of a mean. Biometrika, 6, 1-25.

Swallow, W. H., & Monahan, J. F. (1984). Monte Carlo comparison of ANOVA, MIVQUE, REML, and ML estimators of variance components. Technometrics, 26, 47-57.