Regression Action Set

Albert, A., and Anderson, J. A. (1984). “On the Existence of Maximum Likelihood Estimates in Logistic Regression Models.” Biometrika 71:1–10.

Allison, P. D. (2012). Logistic Regression Using SAS: Theory and Application. 2nd ed. Cary, NC: SAS Institute Inc.

Brier, G. W. (1950). “Verification of Forecasts Expressed in Terms of Probability.” Monthly Weather Review 78:1–3.

Cook, R. D., and Weisberg, S. (1982). Residuals and Influence in Regression. New York: Chapman & Hall.

Cox, D. R., and Snell, E. J. (1989). The Analysis of Binary Data. 2nd ed. London: Chapman & Hall.

Diggle, P. J., Liang, K.-Y., and Zeger, S. L. (1994). Analysis of Longitudinal Data. Oxford: Clarendon Press.

Fagerland, M. W., and Hosmer, D. W. (2013). “A Goodness-of-Fit Test for the Proportional Odds Regression Model.” Statistics in Medicine 32:2235–2249.

Fagerland, M. W., and Hosmer, D. W. (2016). “Tests for Goodness of Fit in Ordinal Logistic Regression Models.” Journal of Statistical Computation and Simulation 86:3398–3418.

Fagerland, M. W., Hosmer, D. W., and Bofin, A. M. (2008). “Multinomial Goodness-of-Fit Tests for Logistic Regression Models.” Statistics in Medicine 27:4238–4253.

Fleiss, J. L., Levin, B., and Paik, M. C. (2003). Statistical Methods for Rates and Proportions. 3rd ed. Hoboken, NJ: John Wiley & Sons.

Gupta, A. K., Nguyen, T., and Pardo, L. (2008). “Residuals for Polytomous Logistic Regression Models Based on -Divergences Test Statistics.” Statistics 42:495–514.

Hardin, J. W., and Hilbe, J. M. (2003). Generalized Estimating Equations. Boca Raton, FL: Chapman & Hall/CRC.

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.

Hosmer, D. W., Jr., and Lemeshow, S. (2000). Applied Logistic Regression. 2nd ed. New York: John Wiley & Sons.

Lesaffre, E., and Albert, A. (1989). “Multiple-Group Logistic Regression Diagnostics.” Journal of the Royal Statistical Society, Series C 38:425–440.

Liang, K.-Y., and Zeger, S. L. (1986). “Longitudinal Data Analysis Using Generalized Linear Models.” Biometrika 73:13–22.

Lipsitz, S. R., Fitzmaurice, G. M., Orav, E. J., and Laird, N. M. (1994). “Performance of Generalized Estimating Equations in Practical Situations.” Biometrics 50:270–278.

Littell, R. C., Freund, R. J., and Spector, P. C. (1991). SAS System for Linear Models. 3rd ed. Cary, NC: SAS Institute Inc.

Magee, L. (1990). “ Measures Based on Wald and Likelihood Ratio Joint Significant Tests.” American Statistician 44:250–253.

Martín, N. (2015). “Using Cook’s Distance in Polytomous Logistic Regression.” British Journal of Mathematical and Statistical Psychology 68:84–115.

McCullagh, P., and Nelder, J. A. (1989). Generalized Linear Models. 2nd ed. London: Chapman & Hall.

McFadden, D. (1974). “Conditional Logit Analysis of Qualitative Choice Behavior.” In Frontiers in Econometrics, edited by P. Zarembka, 105–142. New York: Academic Press.

McNicol, D. (2005). A Primer of Signal Detection Theory. Mahwah, NJ: Lawrence Erlbaum Associates.

Muller, K. E., and Fetterman, B. A. (2002). Regression and ANOVA: An Integrated Approach Using SAS Software. Cary, NC: SAS Institute Inc.

Murphy, A. H. (1973). “A New Vector Partition of the Probability Score.” Journal of Applied Meteorology 12:595–600.

Nagelkerke, N. J. D. (1991). “A Note on a General Definition of the Coefficient of Determination.” Biometrika 78:691–692.

Pan, W. (2001). “Akaike’s Information Criterion in Generalized Estimating Equations.” Biometrics 57:120–125.

Paul, P., Pennell, M. L., and Lemeshow, S. (2013). “Standardizing the Power of the Hosmer-Lemeshow Goodness of Fit Test in Large Data Sets.” Statistics in Medicine 32:67–80.

Pepe, M. S. (2003). The Statistical Evaluation of Medical Tests for Classification and Prediction. New York: Oxford University Press.

Pregibon, D. (1981). “Logistic Regression Diagnostics.” Annals of Statistics 9:705–724.

Preisser, J. S., and Qaqish, B. F. (1996). “Deletion Diagnostics for Generalised Estimating Equations.” Biometrika 83:551–562.

Royall, R. M. (1986). “Model Robust Inference Using Maximum Likelihood Estimators.” International Statistical Review 54:221–226.

Santner, T. J., and Duffy, D. E. (1986). “A Note on A. Albert and J. A. Anderson’s Conditions for the Existence of Maximum Likelihood Estimates in Logistic Regression Models.” Biometrika 73:755–758.

Tjur, T. (2009). “Coefficients of Determination in Logistic Regression Models—a New Proposal: The Coefficient of Discrimination.” American Statistician 63:366–372.

Venzon, D. J., and Moolgavkar, S. H. (1988). “A Method for Computing Profile-Likelihood-Based Confidence Intervals.” Journal of the Royal Statistical Society, Series C 37:87–94.

White, H. (1982). “Maximum Likelihood Estimation of Misspecified Models.” Econometrica 50:1–25.

Williams, D. A. (1987). “Generalized Linear Model Diagnostics Using the Deviance and Single Case Deletions.” Journal of the Royal Statistical Society, Series C 36:181–191.

Zeger, S. L., Liang, K.-Y., and Albert, P. S. (1988). “Models for Longitudinal Data: A Generalized Estimating Equation Approach.” Biometrics 44:1049–1060.