Longitudinal data analysis using the conditional empirical likelihood method

This paper studies a new approach to longitudinal data analysis using the conditional empirical likelihood (CEL) method within the framework of marginal models. The possible unbalanced follow‐up visits are dealt with via stratification according to distinctive follow‐up patterns. The CEL method does not require any explicit modelling of the variance–covariance of the longitudinal outcomes. Instead, it implicitly incorporates a consistently estimated variance–covariance matrix in a nonparametric fashion. The proposed CEL estimator is connected to the generalized estimating equations (GEE) estimator, and achieves the same efficiency as the GEE estimator employing the true variance–covariance. The asymptotic distribution of the CEL estimator is derived, and simulation studies are conducted to assess the finite sample performance. Data collected from a longitudinal nutrition study are analysed as an application. The Canadian Journal of Statistics 42: 404–422; 2014 © 2014 Statistical Society of Canada Résumé Les auteurs proposent une nouvelle approche pour l'analyse de données longitudinales à l'aide de la méthode de la vraisemblance empirique conditionnelle (VEC) dans le cadre de modèles marginaux. Ils prennent en compte la possibilité d'un suivi irrégulier en stratifiant selon les séquences de suivis observées. La VEC ne nécessite pas la modélisation explicite de la variance‐covariance des résultats longitudinaux, mais en intègre plutôt implicitement un estimateur non paramétrique convergent. La VEC est associée aux équations d'estimation généralisées (EEG), et les estimateurs découlant de la VEC atteignent la même efficacité que ceux des EEG basées sur la vraie structure de variance‐covariance. Les auteurs présentent la distribution asymptotique de l'estimateur de la VEC, ainsi qu'une étude de simulation afin d’évaluer la performance de la méthode sur des échantillons finis. Ils effectuent finalement l'analyse des données d'une étude longitudinale portant sur la nutrition. La revue canadienne de statistique 42: 404–422; 2014 © 2014 Société statistique du CanadaPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/108267/1/cjs11221-sm-0001-SupInfo-S1.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/108267/2/cjs11221.pd

Algorithmic Superactivation of Asymptotic Quantum Capacity of Zero-Capacity Quantum Channels

The superactivation of zero-capacity quantum channels makes it possible to use two zero-capacity quantum channels with a positive joint capacity for their output. Currently, we have no theoretical background to describe all possible combinations of superactive zero-capacity channels; hence, there may be many other possible combinations. In practice, to discover such superactive zero-capacity channel-pairs, we must analyze an extremely large set of possible quantum states, channel models, and channel probabilities. There is still no extremely efficient algorithmic tool for this purpose. This paper shows an efficient algorithmical method of finding such combinations. Our method can be a very valuable tool for improving the results of fault-tolerant quantum computation and possible communication techniques over very noisy quantum channels.Comment: 35 pages, 17 figures, Journal-ref: Information Sciences (Elsevier, 2012), presented in part at Quantum Information Processing 2012 (QIP2012), v2: minor changes, v3: published version; Information Sciences, Elsevier, ISSN: 0020-0255; 201

Self-assessment of clinical competence of nursing students' at Slovak universities

Background: Professional training and education of nurses are based on their clinical competences. Competence is an integration of knowledge, skills, and abilities, applied in nursing practice situations. By educating students in nursing, we strive for level of competencies to be consistent with the performance of the nursing profession. Objective: The objective of the study was to analyze nursing students' self-assessment of competence levels at the time of graduation and to identify possible factors related the assessments of competence level. Sample and methodology: The research design had the character of a cross - sectional evaluation study, where The Nurse Competence Scale (NCS) was used to collect data. A total of 310 nursing students before completing the bachelor's degree, participated online to complete the NCS questionnaire, which represented 52.5% of the total number of graduating students at Slovak universities in the academic year 2018/2019. Results: The overall self-assessment of the competence level reached a score of 57.0 (± 15.9; min 45.80, max 70.87), which represents a good level of competence. Statistically significant correlations were confirmed between the higher level of self-assessment of competences and factors related to education and the frequency of their use in practice. Self-assessed competence makes it possible to identify areas that can be further developed and covered it will be necessary to focus on curricula and student training. Conclusion: Systematic self-assessment of competences, allows to assess readiness of nursing students to perform the profession of nurse in accordance with the expectations of practice. It also supports the responsibility of students for monitoring and motivation to study. </p

Maximum Entropy: Clearing up Mysteries

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