Aitken, M. (1987). “Modelling Variance Heterogeneity in Normal Regression Using GLIM.” Journal of the Royal Statistical Society, Series C 36:332–339.
Akaike, H. (1974). “A New Look at the Statistical Model Identification.” IEEE Transactions on Automatic Control AC-19:716–723.
Anderson, T. W. (1958). An Introduction to Multivariate Statistical Analysis. New York: John Wiley & Sons.
Belsley, D. A., Kuh, E., and Welsch, R. E. (1980). Regression Diagnostics: Identifying Influential Data and Sources of Collinearity. New York: John Wiley & Sons.
Benjamini, Y., and Hochberg, Y. (1995). “Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing.” Journal of the Royal Statistical Society, Series B 57:289–300.
Box, G. E. P. (1954). “Some Theorems on Quadratic Forms Applied in the Study of Analysis of Variance Problems, Part 2: Effects of Inequality of Variance and of Correlation between Errors in the Two-Way Classification.” Annals of Mathematical Statistics 25:484–498.
Box, G. E. P., and Cox, D. R. (1964). “An Analysis of Transformations.” Journal of the Royal Statistical Society, Series B 26:211–243.
Box, G. E. P., and Meyer, R. D. (1986). “An Analysis for Unreplicated Fractional Factorials.” Technometrics 28:11–18.
Box, G. E. P., and Meyer, R. D. (1993). “Finding the Active Factors in Fractionated Screening Experiments.” Journal of Quality Technology 25:94–105.
Burnham, K. P., and Anderson, D. R. (2004). “Multimodel Inference: Understanding AIC and BIC in Model Selection.” Sociological Methods and Research 33:261–304.
Burnham, K. P., Andersen, D. R., and Huyvaert, K. P. (2011). “AIC Model Selection and Multimodel Inference in Behavioral Ecology: Some Background, Observations, and Comparisons.” Behavioral Ecology and Sociobiology 65:23–35.
Candes, E., and Tao, T. (2007). “The Dantzig Selector: Statistical Estimation when p is Much Larger than n.” The Annals of Statistics 35:2313–2351.
Carroll, R. J., and Ruppert, D. (1988). Transformation and Weighting in Regression. London: Chapman & Hall.
Chilès, J.-P., and Delfiner, P. (2012). Geostatistics: Modeling Spatial Uncertainty. 2nd ed. New York: John Wiley & Sons.
Cobb, G. W. (1998). Introduction to Design and Analysis of Experiments. New York: Springer-Verlag.
Cohen, J. (1977). Statistical Power Analysis for the Behavioral Sciences. New York: Academic Press.
Cole, J. W. L., and Grizzle, J. E. (1966). “Applications of Multivariate Analysis of Variance to Repeated Measures Experiments.” Biometrics 22:810–828.
Conover, W. J. (1999). Practical Nonparametric Statistics. 3rd ed. New York: John Wiley & Sons.
Cook, R. D., and Weisberg, S. (1982). Residuals and Influence in Regression. New York: Chapman & Hall.
Cook, R. D., and Weisberg, S. (1983). “Diagnostics for Heteroscedasticity in Regression.” Biometrika 70:1–10.
Cornell, J. A. (1990). Experiments with Mixtures. 2nd ed. New York: John Wiley & Sons.
Cox, D. R. (1972). “Regression Models and Life-Tables.” Journal of the Royal Statistical Society, Series B 34:187–220.
Cox, D. R., and Snell, E. J. (1989). The Analysis of Binary Data. 2nd ed. London: Chapman & Hall.
Cressie, N. A. C. (1993). Statistics for Spatial Data. Rev. ed. New York: John Wiley & Sons.
Daniel, C. (1959). “Use of Half-Normal Plots in Interpreting Factorial Two-Level Experiments.” Technometrics 1:311–341.
Dunnett, C. W. (1955). “A Multiple Comparisons Procedure for Comparing Several Treatments with a Control.” Journal of the American Statistical Association 50:1096–1121.
Dwass, M. (1955). “A Note on Simultaneous Confidence Intervals.” Annals of Mathematical Statistics 26:146–147.
Efron, B. (1977). “The Efficiency of Cox’s Likelihood Function for Censored Data.” Journal of the American Statistical Association 72:557–565.
Farebrother, R. W. (1987). “Mechanical Representations of the L1 and L2 Estimation Problems.” In Statistical Data Analysis Based on L1 Norm and Related Methods, edited by Y. Dodge, 455–464. Amsterdam: North-Holland.
Fieller, E. C. (1954). “Some Problems in Interval Estimation.” Journal of the Royal Statistical Society, Series B 16:175–185.
Firth, D. (1993). “Bias Reduction of Maximum Likelihood Estimates.” Biometrika 80:27–38.
Fleming, T. R., and Harrington, D. P. (1991). Counting Processes and Survival Analysis. New York: John & Sons.
Goodnight, J. H. (1978). Tests of Hypotheses in Fixed Effects Linear Models. Technical Report R–101, SAS Institute Inc., Cary, NC.
Goodnight, J. H., and Harvey, W. R. (1978). Least-Squares Means in the Fixed-Effects General Linear Models. Technical Report R-103, SAS Institute Inc., Cary, NC.
Goos, P., and Jones, B. (2011). Optimal Design of Experiments: A Case Study Approach. Chichester, UK: John Wiley & Sons.
Greenhouse, S. W., and Geisser, S. (1959). “On Methods in the Analysis of Profile Data.” Psychometrika 32:95–112.
Harrell, F. E. (1986). “The LOGIST Procedure.” In SUGI Supplemental Library Guide, Version 5 Edition. Cary, NC: SAS Institute Inc.
Harvey, A. C. (1976). “Estimating Regression Models with Multiplicative Heteroscedasticity.” Econometrica 44:461–465.
Hastie, T. J., Tibshirani, R. J., and Friedman, J. H. (2009). The Elements of Statistical Learning: Data Mining, Inference, and Prediction. 2nd ed. New York: Springer-Verlag.
Hayter, A. J. (1984). “A Proof of the Conjecture That the Tukey-Kramer Method Is Conservative.” Annals of Statistics 12:61–75.
Heinze, G., and Schemper, M. (2002). “A Solution to the Problem of Separation in Logistic Regression.” Statistics in Medicine 21:2409–2419.
Hocking, R. R. (1985). The Analysis of Linear Models. Monterey, CA: Brooks/Cole.
Hoenig, J. M., and Heisey, D. M. (2001). “The Abuse of Power: The Pervasive Fallacy of Power Calculations for Data Analysis.” American Statistician 55:19–24.
Hoerl, A. (1962). “Application of Ridge Analysis to Regression Problems.” Chemical Engineering Progress 58:54–59.
Hoerl, A., and Kennard, R. (1970). “Ridge Regression: Biased Estimation for Non-orthogonal Problems.” Technometrics 12:55–67.
Hsu, J. C. (1992). “The Factor Analytic Approach to Simultaneous Inference in the General Linear Model.” Journal of Computational and Graphical Statistics 1:151–168.
Hsu, J. C. (1996). Multiple Comparisons: Theory and Methods. London: Chapman & Hall.
Hu, W., Laber, E. B., Barker, C., and Stefanski, L. A. (2019. “Assessing Tuning Parameter Selection Variability in Penalized Regression.” Technometrics 61:154–164.
Huber, P. J., and Ronchetti, E. M. (2009). Robust Statistics. 2nd ed. John Wiley & Sons.
Hui, F., Warton, D., and Foster, S. (2015). “Tuning Parameter Selection for the Adaptive Lasso Using ERIC.” Journal of the American Statistical Association 110:262–269.
Huynh, H., and Feldt, L. S. (1970). “Conditions Under Which Mean Square Ratios in Repeated Measurements Designs Have Exact F-Distributions.” Journal of the American Statistical Association 65:1582–1589.
Huynh, H., and Feldt, L. S. (1976). “Estimation of the Box Correction for Degrees of Freedom from Sample Data in the Randomized Block and Split Plot Designs.” Journal of Educational Statistics 1:69–82.
Kackar, R. N., and Harville, D. A. (1984). “Approximations for Standard Errors of Estimators of Fixed and Random Effects in Mixed Linear Models.” Journal of the American Statistical Association 79:853–862.
Kalbfleisch, J. D., and Prentice, R. L. (2002). The Statistical Analysis of Failure Time Data. 2nd ed. Hoboken, NJ: John Wiley & Sons.
Kenward, M. G., and Roger, J. H. (1997). “Small Sample Inference for Fixed Effects from Restricted Maximum Likelihood.” Biometrics 53:983–997.
Koenker, R., and Hallock, K. (2001). “Quantile Regression: An Introduction.” Journal of Economic Perspectives 15:143–156.
Kramer, C. Y. (1956). “Extension of Multiple Range Tests to Group Means with Unequal Numbers of Replications.” Biometrics 12:307–310.
Lenth, R. V. (1989). “Quick and Easy Analysis of Unreplicated Factorials.” Technometrics 31:469–473.
Littell, R. C., Milliken, G. A., Stroup, W. W., Wolfinger, R. D., and Schabenberger, O. (2006). SAS for Mixed Models. 2nd ed. Cary, NC: SAS Institute Inc.
Mallows, C. L. (1973). “Some Comments on Cp.” Technometrics 15:661–675.
Mardia, K. V., Kent, J. T., and Bibby, J. M. (1979). Multivariate Analysis. London: Academic Press.
McClave, J. T., and Dietrich, F. H. (1988). Statistics. San Francisco: Dellen.
McCullagh, P., and Nelder, J. A. (1989). Generalized Linear Models. 2nd ed. London: Chapman & Hall.
McCulloch, C. E., Searle, S. R., and Neuhaus, J. M. (2008). Generalized, Linear, and Mixed Models. New York: John Wiley & Sons.
Meeker, W. Q., and Escobar, L. A. (1998). Statistical Methods for Reliability Data. New York: John Wiley & Sons.
Miller, A. J. (1990). Subset Selection in Regression. New York: Chapman & Hall.
Montgomery, D. C. (1991). “Using Fractional Factorial Designs for Robust Process Development.” Quality Engineering 3:193–205.
Muller, K. E., and Barton, C. N. (1989). “Approximate Power for Repeated-Measures ANOVA Lacking Sphericity.” Journal of the American Statistical Association 84:549–555. Also see “Correction to ‘Approximate Power for Repeated-Measures ANOVA Lacking Sphericity’,” Journal of the American Statistical Association 86 (1991): 255–256.
Nagelkerke, N. J. D. (1991). “A Note on a General Definition of the Coefficient of Determination.” Biometrika 78:691–692.
Nelder, J. A., and Wedderburn, R. W. M. (1972). “Generalized Linear Models.” Journal of the Royal Statistical Society, Series A 135:370–384.
Nelson, F. D. (1976). “On a General Computer Algorithm for the Analysis of Models with Limited Dependent Variables.” Annals of Economic and Social Measurement 5:493–509.
Nelson, P. R., Wludyka, P. S., and Copeland, K. A. F. (2005). The Analysis of Means: A Graphical Method for Comparing Means, Rates, and Proportions. Philadelphia: SIAM.
Patterson, H. D., and Thompson, R. (1974). “Maximum Likelihood Estimation of Components of Variance.” In Proceedings of the Eighth International Biometric Conference, 197–207. Washington, DC: International Biometric Society.
Portnoy, S., and Koenker, R. (1997). “The Gaussian Hare and the Laplacian Tortoise: Computation of Squared-Error vs. Absolute-Error Estimators.” Statistical Science 12:279–300.
Rawlings, J. O. (1988). Applied Regression Analysis: A Research Tool. Pacific Grove, CA: Wadsworth & Brooks/Cole Advanced Books & Software.
Ries, P. N., and Smith, H. (1963). “The Use of Chi-Square for Preference Testing in Multidimensional Problems.” Chemical Engineering Progress 59:39–43.
Sall, J. P. (1990). “Leverage Plots for General Linear Hypotheses.” American Statistician 44:308–315.
SAS Institute Inc. (2020a). “The GENMOD Procedure.” In SAS/STAT 15.2 User’s Guide. Cary, NC: SAS Institute Inc. https://go.documentation.sas.com/api/docsets/statug/15.2/content/genmod.pdf.
SAS Institute Inc. (2020b). “The GLM Procedure.” In SAS/STAT 15.2 User’s Guide. Cary, NC: SAS Institute Inc. https://go.documentation.sas.com/api/docsets/statug/15.2/content/glm.pdf.
SAS Institute Inc. (2020c). “Introduction to Statistical Modeling with SAS/STAT Software.” In SAS/STAT 15.2 User’s Guide. Cary, NC: SAS Institute Inc. https://go.documentation.sas.com/api/docsets/statug/15.2/content/intromod.pdf.
SAS Institute Inc. (2020d). “The MIXED Procedure.” In SAS/STAT 15.2 User’s Guide. Cary, NC: SAS Institute Inc. https://go.documentation.sas.com/api/docsets/statug/15.2/content/mixed.pdf.
Satterthwaite, F. E. (1946). “An Approximate Distribution of Estimates of Variance Components.” Biometrics Bulletin 2:110–114.
Scheffé, H. (1958). “Experiments with Mixtures.” Journal of the Royal Statistical Society, Series B 20:344–360.
Schuirmann, D. J. (1987). “A Comparison of the Two One-Sided Tests Procedure and the Power Approach for Assessing the Equivalence of Average Bioavailability.” Journal of Pharmacokinetics and Biopharmaceutics 15:657–680.
Searle, S. R., Casella, G., and McCulloch, C. E. (1992). Variance Components. New York: John Wiley & Sons.
Seber, G. A. F. (1984). Multivariate Observations. New York: John Wiley & Sons.
Singer, J. D. (1998). “Using SAS PROC MIXED to Fit Multilevel Models, Hierarchical Models, and Individual Growth Models.” Journal of Educational and Behavioral Statistics 23:323–355.
Snedecor, G. W., and Cochran, W. G. (1967). Statistical Methods. 6th ed. Ames: Iowa State University Press.
Spiller, S. A., Fitzsimons, G. J., Lynch, J. G., Jr., and McClelland, G. (2013). “Spotlights, Floodlights, and the Magic Number Zero: Simple Effects Tests in Moderated Regression.” Journal of Marketing Research 50:277–288.
Stone, C., and Koo, C. Y. (1985). “Additive Splines in Statistics.” In Proceedings of the Statistical Computing Section, 45–48. Alexandria, VA: American Statistical Association.
Sullivan, L. M., Dukes, K. A., and Losina, E. (1999). “An Introduction to Hierarchical Linear Modelling.” Statistics in Medicine 18:855–888.
Tibshirani, R. (1996). “Regression Shrinkage and Selection via the Lasso.” Journal of the Royal Statistical Society, Series B 58:267–288.
Tukey, J. W. (1953). “The Problem of Multiple Comparisons.” In Multiple Comparisons, 1948–1983, edited by H. I. Braun, vol. 8 of The Collected Works of John W. Tukey (published 1994), 1–300. London: Chapman & Hall. Unpublished manuscript.
Walker, S. H., and Duncan, D. B. (1967). “Estimation of the Probability of an Event as a Function of Several Independent Variables.” Biometrika 54:167–179.
Westfall, P. H., Tobias, R. D., and Wolfinger, R. D. (2011). Multiple Comparisons and Multiple Tests Using SAS. 2nd ed. Cary, NC: SAS Institute Inc.
Wilks, S. S. (1938). “The Large-Sample Distribution of the Likelihood Ratio for Testing Composite Hypotheses.” Annals of Mathematical Statistics. 9:60–62.
Wolfinger, R. D., Tobias, R. D., and Sall, J. (1994). “Computing Gaussian Likelihoods and Their Derivatives for General Linear Mixed Models.” SIAM Journal on Scientific Computing 15:1294–1310.
Wright, S. P., and O’Brien, R. G. (1988). “Power Analysis in an Enhanced GLM Procedure: What it Might Look Like.” In Proceedings of the Thirteenth Annual SAS Users Group International Conference, 1097–1102. Cary, NC: SAS Institute Inc. http://www.sascommunity.org/sugi/SUGI88/Sugi-13-220%20Wright%20OBrien.pdf.
Zou, H. (2006). “The Adaptive Lasso and Its Oracle Properties.” Journal of the American Statistical Association 101:1418–1429.
Zou, H., and Hastie, T. (2005). “Regularization and Variable Selection via the Elastic Net.” Journal of the Royal Statistical Society, Series B 67:301–320.