Making any type of decision, from buying a car to siting a nuclear plant, from choosing the best student deserving a scholarship to ranking the cities of the world according to their liveability, involves the evaluation of several alternatives with respect to different aspects, technically called evaluation criteria. Multiple Criteria Decision Aiding (MCDA) (see [13, 14]) provides methodologies...

The performance of medical image classification has been enhanced by deep convolutional neural networks (CNNs), which are typically trained with cross-entropy (CE) loss. However, when the label presents an intrinsic ordinal property in nature, e.g., development from benign to malignant tumor, CE loss cannot take into account such information allow for better generalization. To improve model gen...

There are a number of reasonable approaches to analysing an ordinal outcome variable. One common approach, known as the Proportional Odds (PO) Model, is implemented in Stata as ologit. If the assumptions of the PO model are not satisfied, an alternative is to treat the outcome as categorical, rather than ordinal, and use multinomial logistic regression (mlogit) in Stata. This insert describes a...

©FSRH J Fam Plann Reprod Health Care 2008: 34(3) What is it? When a response variable has only two possible values (e.g. recurrence/not), binary logistic regression is commonly used to test or model the association between that response and a number of potential explanatory variables, with each association estimated in terms of an odds ratio (OR). Multinomial logistic regression is an extension...