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Journal of the Royal Statistical Society. Series A, (Statistics in Society)|June 30, 2010
Joint generalized estimating equations for multivariate longitudinal binary outcomes with missing data: An application to AIDS dataStuart R Lipsitz, Garrett M Fitzmaurice, Joseph G Ibrahim, et al.Biostatistics (Oxford, England)|April 8, 2014
Almost efficient estimation of relative risk regressionGarrett M Fitzmaurice, Stuart R Lipsitz, Alex Arriaga, et al.Biometrics|March 13, 2015
Testing for independence in J×K contingency tables with complex sample survey dataStuart R Lipsitz, Garrett M Fitzmaurice, Debajyoti Sinha, et al.Clinical Gastroenterology and Hepatology : the Official Clinical Practice Journal of the American Gastroenterological Association|May 5, 2007
Endoscopic ultrasound: a meta-analysis of test performance in suspected biliary obstructionDonald Garrow, Scott Miller, Debajyoti Sinha, et al.Statistical Methods in Medical Research|August 13, 2015
Bias-corrected estimates for logistic regression models for complex surveys with application to the United States' Nationwide Inpatient SampleKevin A Rader, Stuart R Lipsitz, Garrett M Fitzmaurice, et al.Statistics in Medicine|March 6, 2010
A weighted combination of pseudo-likelihood estimators for longitudinal binary data subject to non-ignorable non-monotone missingnessAndrea B Troxel, Stuart R Lipsitz, Garrett M Fitzmaurice, et al.Journal of the Royal Statistical Society. Series C, Applied Statistics|August 6, 2013
An extension of the Wilcoxon Rank-Sum test for complex sample survey dataSundar Natarajan, Stuart R Lipsitz, Garrett M Fitzmaurice, et al.Journal of the Royal Statistical Society. Series C, Applied Statistics|June 10, 2021
Using Cox regression to develop linear rank tests with zero-inflated clustered dataStuart R Lipsitz, Garrett M Fitzmaurice, Debajyoti Sinha, et al.The Annals of Applied Statistics|May 3, 2011
A generalized linear mixed model for longitudinal binary data with a marginal logit link functionMichael Parzen, Souparno Ghosh, Stuart Lipsitz, et al.Journal of the Royal Statistical Society. Series C, Applied Statistics|August 6, 2013
Bias correction for the proportional odds logistic regression model with application to a study of surgical complicationsStuart R Lipsitz, Garrett M Fitzmaurice, Scott E Regenbogen, et al.Pageof 12