Reducing Acute Care Using a Community Care Coordination Network. - William P. Moran; Catherine H. Messick; James L. Wofford; John S. Preisser; G. John Chen; Arden Sheehan; Dorothy L. Currin; Greg Russell; Mark Wright; Ramon Velez (AMIA, 1997)

7 Generalized linear models for independent and dependent responses. - Bahjat F. Qaqish; John S. Preisser (Bioenvironmental and public health statistics, 2000)

Alternative computational formulae for generalized linear model diagnostics: identifying influential observations with SAS software. - John S. Preisser; Daniel I. Garcia (Comput. Stat. Data Anal., 2005)

A SAS/IML software program for GEE and regression diagnostics. - Bradley G. Hammill; John S. Preisser (Comput. Stat. Data Anal., 2006)

Deletion diagnostics for marginal mean and correlation model parameters in estimating equations. - John S. Preisser; Jamie Perin (Stat. Comput., 2007)

ORTH: R and SAS software for regression models of correlated binary data based on orthogonalized residuals and alternating logistic regressions. - Kunthel By; Bahjat F. Qaqish; John S. Preisser; Jamie Perin; Richard C. Zink (Comput. Methods Programs Biomed., 2014)

GEEORD: A SAS macro for analyzing ordinal response variables with repeated measures through proportional odds, partial proportional odds, or non-proportional odds models. - Xiaoming Gao; Todd A. Schwartz; John S. Preisser; Jamie Perin (Comput. Methods Programs Biomed., 2017)

GEECORR: A SAS macro for regression models of correlated binary responses and within-cluster correlation using generalized estimating equations. - Tracie L. Shing; John S. Preisser; Richard C. Zink (Comput. Methods Programs Biomed., 2021)

GEEMAEE: A SAS macro for the analysis of correlated outcomes based on GEE and finite-sample adjustments with application to cluster randomized trials. - Ying Zhang; John S. Preisser; Fan Li; Elizabeth Turner; Mark Toles; Paul J. Rathouz (Comput. Methods Programs Biomed., 2023)

ORTH.Ord: An R package for analyzing correlated ordinal outcomes using alternating logistic regressions with orthogonalized residuals. - Can Meng; Mary Ryan; Paul J. Rathouz; Elizabeth Turner; John S. Preisser; Fan Li (Comput. Methods Programs Biomed., 2023)