Estimating a survival function with incomplete cause-of-death data

Estimating the Net Survival of Patients with Gastric Cancer in Iran in a Relative Survival Framework

Background: Iran is an Eastern Mediterranean region country with the highest rate of gastric cancer. The present study aimed to evaluate the 5-year net survival of patients with gastric cancer in Iran using a relative survival framework.Methods: In a cross-sectional study, using life-table estimation of relative survival, we reported 1- to 5-year relative survival regarding age, sex, disease st...

Assessment of the Data Quality of Cause of Death Registration in Iranian Hospitals in 2016

Background and Objectives: A large proportion of the data of cause of death is registered in hospitals in Iran. Assessment of the death data can help to identify the problems of cause of death registration system and improve it. Therefore, this study was conducted to review the quality of cause of death registration in Iranian hospitals in 2016.   Methods: All hospital deaths in 2016 were rev...

Marginal Analysis of A Population-Based Genetic Association Study of Quantitative Traits with Incomplete Longitudinal Data

A common study to investigate gene-environment interaction is designed to be longitudinal and population-based. Data arising from longitudinal association studies often contain missing responses. Naive analysis without taking missingness into account may produce invalid inference, especially when the missing data mechanism depends on the response process. To address this issue in the ana...

Image Reconstruction from Incomplete Data

Survival Analysis of Gastric Cancer Patients with Incomplete Data

PURPOSE Survival analysis of gastric cancer patients requires knowledge about factors that affect survival time. This paper attempted to analyze the survival of patients with incomplete registered data by using imputation methods. MATERIALS AND METHODS Three missing data imputation methods, including regression, expectation maximization algorithm, and multiple imputation (MI) using Monte Carl...