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A Scaled Linear Mixed Model for Multiple Outcomes

Lin, Xihong; Ryan, Louise; Sammel, Mary; Zhang, Daowen; … - In: Biometrics 56 (2000) 2, pp. 593-601

Persistent link: https://www.econbiz.de/10010946530

Smoothing Spline-Based Score Tests for Proportional Hazards Models

Lin, Jiang; Zhang, Daowen; Davidian, Marie - In: Biometrics 62 (2006) 3, pp. 803-812

Persistent link: https://www.econbiz.de/10010946616

Tzeng, Jung-Ying; Zhang, Daowen; Chang, Sheng-Mao; … - In: Biometrics 65 (2009) 3, pp. 822-832

Persistent link: https://www.econbiz.de/10010946801

Conditional Estimation for Generalized Linear Models When Covariates Are Subject-Specific Parameters in a Mixed Model for Longitudinal Measurements

Li, Erning; Zhang, Daowen; Davidian, Marie - In: Biometrics 60 (2004) 1, pp. 1-7

Persistent link: https://www.econbiz.de/10010946983

Semiparametric Regression for Periodic Longitudinal Hormone Data from Multiple Menstrual Cycles

Zhang, Daowen; Lin, Xihong; Sowers, MaryFran - In: Biometrics 56 (2000) 1, pp. 31-39

Persistent link: https://www.econbiz.de/10010947036

Variable Selection for Semiparametric Mixed Models in Longitudinal Studies

Ni, Xiao; Zhang, Daowen; Zhang, Hao Helen - In: Biometrics 66 (2010) 1, pp. 79-88

Persistent link: https://www.econbiz.de/10010947340

Generalized Linear Mixed Models with Varying Coefficients for Longitudinal Data

Zhang, Daowen - In: Biometrics 60 (2004) 1, pp. 8-15

Persistent link: https://www.econbiz.de/10010947643

Linear Mixed Models with Flexible Distributions of Random Effects for Longitudinal Data

Zhang, Daowen; Davidian, Marie - In: Biometrics 57 (2001) 3, pp. 795-802

Persistent link: https://www.econbiz.de/10010947727

Two-Stage Functional Mixed Models for Evaluating the Effect of Longitudinal Covariate Profiles on a Scalar Outcome

Zhang, Daowen; Lin, Xihong; Sowers, MaryFran - In: Biometrics 63 (2007) 2, pp. 351-362

Persistent link: https://www.econbiz.de/10010948133

Flexible modeling of survival data with covariates subject to detection limits via multiple imputation

Bernhardt, Paul W.; Wang, Huixia Judy; Zhang, Daowen - In: Computational Statistics & Data Analysis 69 (2014) C, pp. 81-91

Models for survival data generally assume that covariates are fully observed. However, in medical studies it is not uncommon for biomarkers to be censored at known detection limits. A computationally-efficient multiple imputation procedure for modeling survival data with covariates subject to...

Persistent link: https://www.econbiz.de/10010871308