Quantile regression (QR) models are one of the methods for longitudinal data analysis. When responses seemto be skew and asymmetric due to outliers heavy-tails, QR may work suitably. This paper developes semi-parametric quantile model analyzing continuous ordinal mixed responses. The latent variable some threshold parameters used perform model’s part. error has Asymmetric Laplace (AL) distribut...

We consider a mixture model approach to the regression analysis of competing-risks data. Attention is focused on inference concerning the effects of factors on both the probability of occurrence and the hazard rate conditional on each of the failure types. These two quantities are specified in the mixture model using the logistic model and the proportional hazards model, respectively. We propos...

All developed countries are facing the problem of providing affordable and high quality healthcare in recent years. This is due to combination an ageing population technological advancement health science which leads increased life expectancy. will affect future use hospital inpatient outpatient services turn place a significant stress on economy since most medical for elderly apportioned funde...

survival analysis is a set of methods used for analysis of the data which exist until the occurrence of an event. this study aimed to compare the results of the use of the semi-parametric cox model with parametric models to determine the factors influencing the length of stay of patients in the inpatient units of women hospital in tehran, iran. in this historical cohort study all 3421 charts of...

We consider the problem of modeling the mean function in regression. Often there is enough knowledge to model some components of the mean function parametrically. But for other vague and/or nuisance components, it is often desirable to leave them unspecified and to be modeled nonparametrically. In this article, we propose a general class of smoothing spline semi-parametric nonlinear regression ...

Non-parametric and semi-parametric analysis of panel count data have recently been an active research topic in statistical literature. Maximum likelihood method based on non-homogeneous Poisson process has been proved an efficient inference procedure for such analysis. However, computing the nonand semi-parametric maximum likelihood estimates (MLE) can be very intensive numerically. In this man...

We consider the estimation of parameters in a particular segmented generalized linear model with additive measurement error in predictors, with a focus on linear and logistic regression. In epidemiologic studies segmented regression models often occur as threshold models, where it is assumed that the exposure has no influence on the response up to a possibly unknown threshold. Furthermore, in o...

Background Central to the study of populations, and therefore to the analysis of the development of countries undergoing major transitions, is the calculation of fertility patterns and their dependence on different variables such as age, education, and socio-economic status. Most epidemiological research on these matters rely on the often unjustified assumption of (generalised) linearity, or al...