We apply the nonconcave penalized likelihood approach to obtain variable selections as well as shrinkage estimators. This approach relies heavily on the choice of regularization parameter, which controls the model complexity. In this paper, we propose employing the generalized information criterion (GIC), encompassing the commonly used Akaike information criterion (AIC) and Bayesian information...

Correlated response data are common in biomedical studies. Regression analysis based on the generalized estimating equations (GEE) is an increasingly important method for such data. However, there seem to be few model-selection criteria available in GEE. The well-known Akaike Information Criterion (AIC) cannot be directly applied since AIC is based on maximum likelihood estimation while GEE is ...

We consider approximate Bayesian model choice for model selection problems that involve models whose Fisher-information matrices may fail to be invertible along other competing submodels. Such singular models do not obey the regularity conditions underlying the derivation of Schwarz’s Bayesian information criterion (BIC) and the penalty structure in BIC generally does not reflect the frequentis...

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...

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...

the logistic, gompertz, richards and asymmetric logistic growth curve models were fitted to body weight data of local ghanaian chickens and french sasso t44 chickens. all four growth models provided good fit for each sex by genotype growth data with r2 values ranging from 86.7% to 96.7%. the rate constant parameter, k, ranged between 0.137 and 0.271 and were significantly different from zero fo...