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Journal of Biopharmaceutical Statistics|October 17, 2014
A Simple Approach for Sample Size Calculation for Comparing Two Concordance Correlation Coefficients Estimated on the Same SubjectsHung-Mo Lin, John M WilliamsonStatistics in Medicine|July 4, 2006
A practical approach to computing power for generalized linear models with nominal, count, or ordinal responsesRobert H Lyles, Hung-Mo Lin, John M WilliamsonStatistics in Medicine|May 21, 2009
Power and sample size calculations for current status survival analysisJohn M Williamson, Hung-Mo Lin, Hae-Young KimBiometrical Journal. Biometrische Zeitschrift|March 20, 2023
A censored quantile regression approach for relative survival analysis: Relative survival quantile regressionJohn M Williamson, Hung-Mo Lin, Robert H LylesJournal of Biopharmaceutical Statistics|March 19, 2004
Design and analytic considerations for single-armed studies with misclassification of a repeated binary outcomeRobert H Lyles, Hung-Mo Lin, John M WilliamsonControlled Clinical Trials|October 24, 2002
Bias in a placebo-controlled study due to mismeasurement of disease status and the regression effectHung-Mo Lin, Robert H Lyles, John M WilliamsonJournal of Biopharmaceutical Statistics|July 7, 2007
Resampling dependent concordance correlation coefficientsJohn M Williamson, Sara B Crawford, Hung-Mo LinStatistics in Medicine|December 9, 2015
Power and sample size calculations for interval-censored survival analysisHae-Young Kim, John M Williamson, Hung-Mo LinStatistics in Medicine|November 16, 2004
Estimation of the intervention effect in a non-randomized study with pre- and post-mismeasured binary responsesHung-Mo Lin, Robert H Lyles, John M Williamson, et al.Biometrics|March 2, 2005
Extending McNemar's test: estimation and inference when paired binary outcome data are misclassifiedRobert H Lyles, John M Williamson, Hung-Mo Lin, et al.Pageof 25