Chen, H. Y. and Li, M.
(2011). Improving power
for detecting genetic association in extreme value sampling design. Accepted by Genetic Epidemiology.
Chen, H. Y. and Chen J. (2011).
On information coded in
gene-environment independence in case-control design. American Journal of
Epidemiology, In press.
Chen, H. Y., Xie, H., and Qian, Y. (2011).
Multiple imputation for missing values through
conditional semiparametric odds ratio models. Biometrics. In press.
Chen, H. Y. (2011). A unified framework for parameter identification and estimation in
biased sampling design. Biometrika 98,
163-175.
Chen, H. Y. (2010). On L^infty convergence of Neumann
series approximation in missing data problems. Probability & Statistics Letters,
80, 864-873.
Chen, H. Y. (2010). Compatibility of conditionally specified distributions.
Probability & Statistics Letters,
80, 670-677.
Chen, H. Y. (2011). Representations of efficient score for coarse data problem based
on Neumann series expansion. The Annals of the Institute of Statistical
Mathematics, 63, 497-509.
Chen, H. Y. (2009).
Estimation and inference based on Neumann series approximation to locally
efficient score in missing data problems. The Scandinavian Journal of Statistics,
36, 713-734. Supplementary material.
Chen, H. Y. and Gao, S. (2009). Estimation of
average treatment effect with incompletely observed longitudinal data:
application to a smoking cessation study. Statistics in Medicine, 28, 2451-2472.
Chen, H. Y. (2007). A semiparametric odds ratio model for measuring association.
Biometrics, 63, 413-421.
See SAID
package for software to perform the proposed analysis.
Chen, H. Y. (2004). Nonparametric and Semiparametric models
for missing covariates in parametric regression.
Journal of the American
Statistical Association, 99, 1176-1189.
See SAID package for software to perform the proposed analysis
Chen, H. Y. (2003). A note on the prospective analysis of outcome-dependent samples. The Journal of Royal
Statistical Society, Series B 575-584.
Chen, H. Y. (2002). Double nonparametric likelihood method for the Cox regression model
with missing covariates. The Journal of American
Statistical Association 97, 565-576.
Chen, H. Y. (2001). Weighted likelihood methods for fitting proportional odds
regression model to case-cohort designs. The Journal of American
Statistical Association 96, 1446-1457.
Chen, H. Y. and Little,R.J.A. (2001). A profile conditional likelihood approach for semiparametric
transformation model with missing covariates.
Lifetime Data Analysis 7,
207-224.
Chen, H. Y. (2001). Analysis of data from the modified case-cohort design by semiparametric transformation regression models. Biometrika 88, 255-268.
Wang, C. Y. and Chen, H. Y.
(2001). Augmented inverse probability weighted
estimator for Cox missing covariate regression. Biometrics 57, 414-419.
Chen, H. Y. and Little,
R.J.A (1999). A test of missing completely
at random for generalized estimating equations with missing data. Biometrika,
86, 1-13.
Chen,H.
Y. and Little, R.J.A. (1999). Proportional hazards
regression with missing covariate. The Journal of American
Statistical Association, 94, 896-908.