Effects of ignoring baseline on modeling transitions from intact cognition to dementia
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- Saskia Litière & Ariel Alonso & Geert Molenberghs, 2007. "Type I and Type II Error Under Random-Effects Misspecification in Generalized Linear Mixed Models," Biometrics, The International Biometric Society, vol. 63(4), pages 1038-1044, December.
- Thomas R. Ten Have & Michael E. Miller & Beth A. Reboussin & Margaret K. James, 2000. "Mixed Effects Logistic Regression Models for Longitudinal Ordinal Functional Response Data with Multiple-Cause Drop-Out from the Longitudinal Study of Aging," Biometrics, The International Biometric Society, vol. 56(1), pages 279-287, March.
- Patrick J. Heagerty, 1999. "Marginally Specified Logistic-Normal Models for Longitudinal Binary Data," Biometrics, The International Biometric Society, vol. 55(3), pages 688-698, September.
- Thomas R. Ten Have & Beth A. Reboussin & Michael E. Miller & Allen Kunselman, 2002. "Mixed Effects Logistic Regression Models for Multiple Longitudinal Binary Functional Limitation Responses with Informative Drop-Out and Confounding by Baseline Outcomes," Biometrics, The International Biometric Society, vol. 58(1), pages 137-144, March.
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- Wei, Shaoceng & Xu, Liou & Kryscio, Richard J., 2014. "Markov transition model to dementia with death as a competing event," Computational Statistics & Data Analysis, Elsevier, vol. 80(C), pages 78-88.
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