Testing Nelder-Mead based repulsion algorithms for multiple roots of nonlinear systems via a two-level factorial design of experiments

This paper addresses the challenging task of computing multiple roots of a system of nonlinear equations. A repulsion algorithm that invokes the Nelder-Mead (N-M) local search method and uses a penalty-type merit function based on the error function, known as 'erf', is presented. In the N-M algorithm context, different strategies are proposed to enhance the quality of the solutions and improve the overall efficiency. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm.

Validation of the Portuguese version of the Evidence-Based Practice Questionnaire

OBJECTIVES: To describe the process of translation and linguistic and cultural validation of the Evidence Based Practice Questionnaire for the Portuguese context: Questionário de Eficácia Clínica e Prática Baseada em Evidências (QECPBE). METHOD: A methodological and cross-sectional study was developed. The translation and back translation was performed according to traditional standards. Principal Components Analysis with orthogonal rotation according to the Varimax method was used to verify the QECPBE's psychometric characteristics, followed by confirmatory factor analysis. Internal consistency was determined by Cronbach's alpha. Data were collected between December 2013 and February 2014. RESULTS: 358 nurses delivering care in a hospital facility in North of Portugal participated in the study. QECPBE contains 20 items and three subscales: Practice (α=0.74); Attitudes (α=0.75); Knowledge/Skills and Competencies (α=0.95), presenting an overall internal consistency of α=0.74. The tested model explained 55.86% of the variance and presented good fit: χ2(167)=520.009; p = 0.0001; χ2df=3.114; CFI=0.908; GFI=0.865; PCFI=0.798; PGFI=0.678; RMSEA=0.077 (CI90%=0.07-0.08). CONCLUSION: confirmatory factor analysis revealed the questionnaire is valid and appropriate to be used in the studied context.