BACKGROUND Multi-state models are appropriate for cancer studies such as gastrectomy which have high mortality statistics. These models can be used to better describe the natural disease process. But reaching that goal requires making assumptions like Markov and homogeneity with time. The present study aims to investigate these hypotheses. MATERIALS AND METHODS Data from 330 patients with gas...

background : gastric cancer is the one of the most prevalent reason of cancer-related death in the world. survival of patients after surgery involves identifying risk factors. there are various models to detect the effect of risk factors on patients’ survival. the present study aims at evaluating these models. methods : data from 330 gastric cancer patients diagnosed at the iran cancer institut...

BACKGROUND Gastric cancer is the one of the most prevalent reason of cancer-related death in the world. Survival of patients after surgery involves identifying risk factors. There are various models to detect the effect of risk factors on patients' survival. The present study aims at evaluating these models. METHODS Data from 330 gastric cancer patients diagnosed at the Iran cancer institute ...

Making informed decisions about model adequacy has been an outstanding issue for regression models with discrete outcomes. Standard assessment tools such outcomes (e.g., deviance residuals) often show a large discrepancy from the hypothesized pattern even under true and are not informative, especially when data highly binary). To fill this gap, we propose quasi-empirical residual distribution f...

Regression models based on the log-symmetric family of distributions are particularly useful when response variable is continuous, positive, and asymmetrically distributed. In this article, we propose derive a class new approach to quantile regression using parameterized by means their quantiles. Two Monte Carlo simulation studies conducted utilizing R software. The first one analyzes performan...