On the impact of disproportional samples in credit scoring models: An application to a Brazilian bank data

Statistical methods have been widely employed to assess the capabilities of credit scoring classification models in order to reduce the risk of wrong decisions when granting credit facilities to clients. The predictive quality of a classification model can be evaluated based on measures such as sensitivity, specificity, predictive values, accuracy, correlation coefficients and information theoretical measures, such as relative entropy and mutual information. In this paper we analyze the performance of a naive logistic regression model (Hosmer & Lemeshow, 1989) and a logistic regression with state-dependent sample selection model (Cramer, 2004) applied to simulated data. Also, as a case study, the methodology is illustrated on a data set extracted from a Brazilian bank portfolio. Our simulation results so far revealed that there is no statistically significant difference in terms of predictive capacity between the naive logistic regression models and the logistic regression with state-dependent sample selection models. However, there is strong difference between the distributions of the estimated default probabilities from these two statistical modeling techniques, with the naive logistic regression models always underestimating such probabilities, particularly in the presence of balanced samples. (C) 2012 Elsevier Ltd. All rights reserved.

Towards global consensus on outcome measures for atopic eczema research: results of the HOME II meeting

The use of nonstandardized and inadequately validated outcome measures in atopic eczema trials is a major obstacle to practising evidence-based dermatology. The Harmonising Outcome Measures for Eczema (HOME) initiative is an international multiprofessional group dedicated to atopic eczema outcomes research. In June 2011, the HOME initiative conducted a consensus study involving 43 individuals from 10 countries, representing different stakeholders (patients, clinicians, methodologists, pharmaceutical industry) to determine core outcome domains for atopic eczema trials, to define quality criteria for atopic eczema outcome measures and to prioritize topics for atopic eczema outcomes research. Delegates were given evidence-based information, followed by structured group discussion and anonymous consensus voting. Consensus was achieved to include clinical signs, symptoms, long-term control of flares and quality of life into the core set of outcome domains for atopic eczema trials. The HOME initiative strongly recommends including and reporting these core outcome domains as primary or secondary endpoints in all future atopic eczema trials. Measures of these core outcome domains need to be valid, sensitive to change and feasible. Prioritized topics of the HOME initiative are the identification/development of the most appropriate instruments for the four core outcome domains. HOME is open to anyone with an interest in atopic eczema outcomes research.