background: the two most frequently diagnosed cancers among women worldwide are breast and cervical cancers. the objective of the present study was to classify the different countries based on the death rates from sex specific cancers. methods : in this cross-sectional study, we used dataset regarding death rate from breast, cervical, uterine, and ovarian cancers in 190 countries worldwide repo...

Model-selection criteria such as AIC and BIC are widely used in applied statistics. In recent years, there has been a huge increase in modeling data from large complex surveys, and a resulting demand for versions of AIC and BIC that are valid under complex sampling. In this paper, we show how both criteria can be modified to handle complex samples. We illustrate with two examples, the first usi...

This paper concerns the asymptotic properties of a class of criteria for model selection in linear regression models, which covers the most well known criteria as e.g. MALLOWS' Cp, CV (cross-validation), GCV ( generalized cross-validation), AKAIKE's AIC and FPE as well as SCHWARZ' BIC. These criteria are shown to be consistent in the sense of selecting the true or larger models, assuming i.i.d....

Hidden Markov random fields appear naturally in problems such as image segmentation, where an unknown class assignment has to be estimated from the observations at each pixel. Choosing the probabilistic model that best accounts for the observations is an important first step for the quality of the subsequent estimation and analysis. A commonly used selection criterion is the Bayesian Informatio...

BACKGROUND Admixture analysis of age at onset (AAO) has helped delineating the clinical profile of early onset (EO) bipolar disorder (BD). However, there is scarce evidence comparing the distributional properties of AAO as well as the clinical features of EO BD type 1 (BD1) with EO BD type 2 (BD2). To this end, we studied 515 BD patients (224 BD1, 279 BD2, and 12 BD not otherwise specified [NOS...

The author introduced the “geometric AIC” and the “geometric MDL” as model selection criteria for geometric fitting problems. These correspond to Akaike’s “AIC” and Rissanen’s “BIC”, respectively, well known in the statistical estimation framework. Another criterion well known is Schwarz’ “BIC”, but its counterpart for geometric fitting has been unknown. This paper introduces the corresponding ...

The model selection criteria AIC, BIC and Cp have been proposed for estimation of the rank of coefficient matrix in multivariate linear model. In general, it is known that under a large-sample asymptotic framework AIC and Cp is not consistent, but BIC is consistent. However, we note that these criteria have consistency when the number p of the response variables and the sample size n are large ...

This article considers the analysis of experiment of repeated measures design that is used frequently in medical research. We propose new approach could be used to guide the selection of the covariance structure. We used simulation study to compare six model selection criteria in terms of their ability to identify the right correlated error model with the help of the new approach. The compariso...

Choosing a model with too few parameters can involve making unrealistically simple assumptions and lead to high bias, poor prediction, and missed opportunities for insight. Such models are not flexible enough to describe the sample or the population well. A model with too many parameters can fit the observed data very well, but be too closely tailored to it. Such models may generalize poorly. P...

We extend the basic idea of Schwarz (1978) and develop a generalized Bayesian information criterion for regression model selection. The new criterion relaxes the usually strong distributional assumption associated with Schwarz’s BIC by adopting a Wilcoxon-type dispersion function and appropriately adjusting the penalty term. We establish that the Wilcoxon-type generalized BIC preserves the cons...