Decomposition of the main effects and interaction term by using orthogonal polynomials in multiple non symmetrical correspondence analysis

The multiple non symmetric correspondence analysis (MNSCA) is a useful technique for analyzing a two-way contingency table. In more complex cases, the predictor variables are more than one. In this paper, the MNSCA, along with the decomposition of the Gray–Williams Tau index, in main effects and interaction term, is used to analyze a contingency table with two predictor categorical variables and an ordinal response variable. The Multiple-Tau index is a measure of association that contains both main effects and interaction term. The main effects represent the change in the response variables due to the change in the level/categories of the predictor variables, considering the effects of their addition, while the interaction effect represents the combined effect of predictor categorical variables on the ordinal response variable. Moreover, for ordinal scale variables, we propose a further decomposition in order to check the existence of power components by using Emerson's orthogonal polynomials.     

Testing homogeneity in semiparametric mixture case–control models

Parametric and semiparametric mixture models have been widely used in applications from many areas, and it is often of interest to test the homogeneity in these models. However, hypothesis testing is non standard due to the fact that several regularity conditions do not hold under the null hypothesis. We consider a semiparametric mixture case–control model, in the sense that the density ratio of two distributions is assumed to be of an exponential form, while the baseline density is unspecified. This model was first considered by Qin and Liang (2011 Qin, J., Liang, K.Y. (2011). Hypothesis testing in a mixture case–control model. Biometrics 67(1):182–198.[Crossref], [PubMed], [Web of Science ®] , [Google Scholar], biometrics), and they proposed a modified score statistic for testing homogeneity. In this article, we consider alternative testing procedures based on supremum statistics, which could improve power against certain types of alternatives. We demonstrate the connection and comparison among the proposed and existing approaches. In addition, we provide a unified theoretical justification of the supremum test and other existing test statistics from an empirical likelihood perspective. The finite-sample performance of the supremum test statistics was evaluated in simulation studies.     

损失模拟模型的模拟与检验

为帮助精算师在不同的数据环境下选择最优的准备金评估方法,美国非寿险精算师协会组织开发了一个产生模拟索赔数据的开源软件系统——损失模拟模型,然而损失模拟模型是否能够按指定参数要求产生模拟数据需要进行检验.文章采用不同的参数估计方法和拟合优度检验方法对模拟索赔次数的分布、索赔额的趋势以及不同险种索赔次数之间的相关结构进行了统计检验,结果表明损失模拟模型对索赔次数的分布、索赔额的趋势能够产生一致的模拟,而对索赔次数数据之间相关结构的模拟存在不稳定性.     

Usability in product design--the importance and need for systematic assessment models in product development--Usa-Design Model (U-D) ©

In product design, human factors are considered as an element of differentiation given that today's consumer demands are increasing. Safety, wellbeing, satisfaction, health, effectiveness, efficiency, and other aspects must be effectively incorporated into the product development process. This work proposes a usability assessment model that can be incorporated as an assessment tool. The methodological approach is settled in two stages. First a literature review focus specifically on usability and developing user-centred products. After this, a model of usability named Usa-Design (U-D?) is presented. Consisted of four phases: understanding the use context, pre-preliminary usability assessment (efficiency/effectiveness/satisfaction); assessment of usability principles and results, U-D? features are modular and flexible, allowing principles used in Phase 3 to be changed according to the needs and scenario of each situation. With qualitative/quantitative measurement scales of easy understanding and application, the model results are viable and applicable throughout all the product development process.     

… Do as the Romans do. A model of conformity with the endogenous formation of preferences

This note is an answer to a previous model on conformity in public goods contributions developed by Carpenter (2004), where a population evolution is allowed according to the standard replicator dynamic (Taylor and Jonker, 1978, Maynard Smith, 1982). To confirm his theoretical prediction, Carpenter developed an experiment showing that free riding actually grows faster when agents have the information necessary to conform. The model and the experiment are, however, inherently different, for the time scales of the model are not able to capture the short run convergence of behavior in the experimental laboratory.We here present a model of conformity which offers the same laboratory results as Carpenter without resorting to evolutionary models, and also gives agents the chance to adopt different strategies implying various levels of cooperation.     

Is Household Wealth Sustainable? An Examination of Asset Poverty Reentry After an Exit

This paper analyzed the influence of financial behaviors on the duration out of asset poverty while controlling for households’ life cycle and demographic characteristics. We found evidence for the existence of structural barriers to asset acquisition. Asset accumulation at or above levels equal to nine-months worth of income at the income-poverty level was important for improving a household’s odds of permanently escaping asset poverty, but a linear relationship between asset accumulation and the likelihood of returning to asset poverty did not emerge. Moreover, minimizing debt and diversifying the asset portfolio to include more productive assets were positively related to maintaining assets; but households should also consider the risks associated with portfolio allocations.     

商务模式创新复杂性研究的计算实验方法

商务模式及其创新的复杂性特征决定了商务模式创新研究有必要采用计算实验的方法.分析商务模式创新研究的基本思路,提出应用计算实验的方法研究商务模式创新的方法论基础及其基本框架.分析和比较计算实验与计算机仿真(模拟)的区别与联系,提出应用粒子群优化算法、遗传算法等智能算法和复杂适应系统理论模拟商务模式的演化过程,进而对商务模式创新进行计算实验研究的基本方法.认为基于智能算法的计算实验为商务模式创新复杂性研究提供了有效的方法论、工具和平台,是商务模式创新复杂性研究的根本途径.     

A Quality Risk Management Model Approach for Cell Therapy Manufacturing

International regulatory authorities view risk management as an essential production need for the development of innovative, somatic cell‐based therapies in regenerative medicine. The available risk management guidelines, however, provide little guidance on specific risk analysis approaches and procedures applicable in clinical cell therapy manufacturing. This raises a number of problems. Cell manufacturing is a poorly automated process, prone to operator‐introduced variations, and affected by heterogeneity of the processed organs/tissues and lot‐dependent variability of reagent (e.g., collagenase) efficiency. In this study, the principal challenges faced in a cell‐based product manufacturing context (i.e., high dependence on human intervention and absence of reference standards for acceptable risk levels) are identified and addressed, and a risk management model approach applicable to manufacturing of cells for clinical use is described for the first time. The use of the heuristic and pseudo‐quantitative failure mode and effect analysis/failure mode and critical effect analysis risk analysis technique associated with direct estimation of severity, occurrence, and detection is, in this specific context, as effective as, but more efficient than, the analytic hierarchy process. Moreover, a severity/occurrence matrix and Pareto analysis can be successfully adopted to identify priority failure modes on which to act to mitigate risks. The application of this approach to clinical cell therapy manufacturing in regenerative medicine is also discussed.