Over recent years, semiparametric technique becomes to have more and more applications
in biometrics as evidenced in the number of publications per year. Therefore it is necessary …

Consider a semiparametric regression model Y= Z β+ m (X)+ ϵ, with Y being the response
variable, X and Z being the covariates, β the unknown parameter, m (·) an unknown function …

When addressing semiparametric problems with parametric restrictions (assumptions on the
distribution), the efficient score (ES) of a parameter is often important for generating useful …

Cheng and Wei (2000) proposed a simple inference procedure to estimate regression
coefficients of a semiparametric model for repeated measurements observed at irregularly …

In recent years, the attention of researchers has increased on semi-parametric regression
models, because it is possible to integrate the parametric and non-parametric regression …

In this thesis, we investigate new methods, extending the marginal and mixed effects models
to deal with more practical and complicated cases in longitudinal data. First, to analyze the …

For clinical trials with time-to-event data, statistical inference often employs the constant
hazard ratio assumption. When the hazards are possibly non-proportional, the hazard ratio …

We propose a method for fitting semiparametric models such as the proportional hazards
(PH), additive risks (AR), and proportional odds (PO) models. Each of these semiparametric …

目的放宽经典线性模型中的解释变量的线性假定和探讨半参数回归分析模型.
方法利用最小惩罚二乘原理构造加权惩罚平方和, 通过广义交互有效得分函数自动选择光滑参数 …

Clustered binary data arise in many fields such as epidemiology, toxicology, econometrics
and pharmacokinetics modelling. For instance, in many epidemiological studies the purpose …