Objective Women undergoing IVF cycles should go successfully through multiple points during the procedure (i.e., implantation, clinical pregnancy, no spontaneous abortion and delivery) to achieve live births. On the other there is a need to consider previous reproductive outcomes and as well as the current cycle. In this study, data on multiple cycles and multiple points during the IVF cycle ar...

Based on clustered data with informative cluster size, two efficient estimation methods are proposed for marginal models. In our procedures, the information of within-cluster correlation and minimum cluster size is fully used; this is not the case with the within-cluster re-sampling (WCR) and cluster-weighted generalized estimating equation (CWGEE) methods. When the correlation model is valid a...

This research is motivated by a periodontal disease dataset that possesses certain special features. The consists of clustered current status time-to-event observations with large and varying cluster sizes, where the size associated outcome. Also, heavy censoring present in data even long follow-up time, suggesting presence cured subpopulation. In this paper, we propose computationally efficien...

background: the present study was performed to develop a scoring system for predicting cure status in patients with cutaneous leishmaniasis (cl). materials and methods: this study included 199 patients with cl from skin diseases and leishmaniasis research center (isfahan, iran). data were collected as longitudinal in each visit of patients. we applied ordinal logistic generalized estimating equ...

Ignorance of the mechanisms responsible for the availability of information presents an unusual problem for analysts. It is often the case that the availability of information is dependent on the outcome. In the analysis of cluster data we say that a condition for informative cluster size (ICS) exists when the inference drawn from analysis of hypothetical balanced data varies from that of infer...

The generalized estimating equations (GEE) approach is commonly used to model incomplete longitudinal binary data. When drop-outs are missing at random through dependence on observed responses (MAR), GEE may give biased parameter estimates in the model for the marginal means. A weighted estimating equations approach gives consistent estimation under MAR when the drop-out mechanism is correctly ...

Multi-level models are extensively used for analyzing survey data with design hierarchy matching the model hierarchy. We propose a weighted estimating equations (WEE) approach for two-level models that leads to design-model consistent estimators of model parameters even when the within-cluster sample sizes are small, provided the number of sample clusters is large. A unified approach based on w...

We propose a new method, called the textit{the weighted space method}, for the study of the generalized Hyers-Ulam-Rassias stability. We use this method for a nonlinear functional equation, for Volterra and Fredholm integral operators.