A flexible semiparametric transformation model for survival data

I suggest an extension of the semiparametric transformation model that specifies a time-varying regression structure for the transformation, and thus allows time-varying structure in the data. Special cases include a stratified version of the usual semiparametric transformation model. The model can be thought of as specifying a first order Taylor expansion of a completely flexible baseline. Large sample properties are derived and estimators of the asymptotic variances of the regression coefficients are given. The method is illustrated by a worked example and a small simulation study. A goodness of fit procedure for testing if the regression effects lead to a satisfactory fit is also suggested.     

Understanding and Using Mediators and Moderators

Mediation and moderation are two theories for refining and understanding a causal relationship. Empirical investigation of mediators and moderators requires an integrated research design rather than the data analyses driven approach often seen in the literature. This paper described the conceptual foundation, research design, data analysis, as well as inferences involved in a mediation and/or moderation investigation in both experimental and non-experimental (i.e., correlational) contexts. The essential distinctions between the investigation of mediators and moderators were summarized and juxtaposed in an example of a causal relationship between test difficulty and test anxiety. In addition, the more elaborate models, moderated mediation and mediated moderation, the use of structural equation models, and the problems with model misspecification were discussed conceptually.

Faking it: Personality and individual difference predictors of willingness to buy counterfeit goods

Counterfeiting is now widely regarded as a serious social, economic, and political issue. This study examined demographic, personality, and individual difference predictors of willingness to buy counterfeit goods (WBCG) in a community sample of British adults. Two-hundred and thirty-seven participants completed a questionnaire that assessed their willingness to buy 19 types of counterfeit goods, attitudes towards counterfeiting, material values, Big Five personality traits, and demographics. Structural equation modelling showed that attitudes towards counterfeiting were the strongest predictors of WBCG. In addition, material values predicted both WBCG directly and indirectly through attitudes towards counterfeiting. Older participants showed lower WBCG, although this effect was moderated by participants’ conscientiousness, material values, and attitudes towards counterfeiting. There were no sex differences in WBCG once participants’ age and conscientiousness had been taken into account. These results are discussed in relation to the extant literature on the profiles of consumers who buy counterfeit products.     

应用同伦正则化算法反演二维溶质运移模型中的弥散系数

利用同伦正则化算法探讨了二维对流弥散方程的依赖空间变量的弥散系数反演问题.讨论了初始迭代值、数值微分步长、以及收敛精度对算法实现的影响.数值模拟表明,同伦正则化算法对于此类参数反演问题是一种有效的方法.     

Threshold Estimation for Stochastic Processes with Small Noise

Consider a process satisfying a stochastic differential equation with unknown drift parameter, and suppose that discrete observations are given. It is known that a simple least squares estimator (LSE) can be consistent but numerically unstable in the sense of large standard deviations under finite samples when the noise process has jumps. We propose a filter to cut large shocks from data and construct the same LSE from data selected by the filter. The proposed estimator can be asymptotically equivalent to the usual LSE, whose asymptotic distribution strongly depends on the noise process. However, in numerical study, it looked asymptotically normal in an example where filter was chosen suitably, and the noise was a Lévy process. We will try to justify this phenomenon mathematically, under certain restricted assumptions.     

Model comparison of linear and nonlinear Bayesian structural equation models with dichotomous data

In this article, dichotomous variables are used to compare between linear and nonlinear Bayesian structural equation models. Gibbs sampling method is applied for estimation and model comparison. Statistical inferences that involve estimation of parameters and their standard deviations and residuals analysis for testing the selected model are discussed. Hidden continuous normal distribution (censored normal distribution) is used to solve the problem of dichotomous variables. The proposed procedure is illustrated by a simulation data obtained from R program. Analyses are done by using R2WinBUGS package in R-program.     

The effect of different data structures,sample sizes on model fit measures

In this study, our aim was to investigate the changes of different data structures and different sample sizes on the structural equation modeling and the influence of these factors on the model fit measures. Examining the created structural equation modeling under different data structures and sample sizes, the evaluation of model fit measures were performed with a simulation study. As a result of the simulation study, optimization and negative variance estimation problems have been encountered depending on the sample size and changing correlations. It was observed that these problems disappeared either by increasing the sample size or the correlations between the variables in factor. For upcoming studies, the choice of RMSEA and IFI model fit measures can be suggested in all sample sizes and the correlation values for data sets are ensured the multivariate normal distribution assumption.     

雾霾感知风险与公众应对行为的实证分析

通过在雾霾严重时期收集的大规模问卷调查数据,建立了雾霾感知风险等因素与应对行为之间关系的结构方程模型.分析显示,对环境信息越敏感、雾霾感知风险越大、对雾霾知识了解越多、雾霾感知可控性越大的公众会采取更多的防护与应对措施,他们对相关防护产品的购买意愿也越强.特别是,感知风险在环境信息与应对行为以及环境满意度之间起着重要的中介变量作用,即当雾霾污染引起人们的感知风险时,会促使他们采取更多的应对行为,并且对环境满意度评价产生负面影响.另外,雾霾感知可控性在雾霾知识熟悉度与应对行为以及环境满意度之间起着部分中介变量的作用.     

Effects of key enabling technologies for seru production on sustainable performance

Demand uncertainty, economic globalization, and environmental deterioration force factories to innovate their manufacturing systems for achieving sustainable performance. Seru production, which is the latest manufacturing mode developed in Japan, attracts broad attention from both academia and practitioners. The overwhelming majority of existing works on seru production focus on economic performance unilaterally, while neglecting the environmental and social performance. This paper investigates the effects of key enabling technologies for seru production on sustainable performance. Firstly, four key enabling technologies for seru production are identified through systematic review, and an evaluation indicator system of sustainable performance in the context of seru production is developed. Then, the hypotheses about the effects of the identified key enabling technologies for seru production on sustainable performance are proposed on the basis of previous research achievements, theoretical analysis, and practical observations. Finally, the hypotheses are tested through structural equation modeling. Except for two hypotheses which are not supported and one which is indirectly supported, all other hypotheses are verified. The research results show that the four key enabling technologies for seru production have different effects on the three dimensions of sustainable performance. The achievements of this work are of significance to improve the comprehensive understanding of seru production, as well as to develop practical methods to implement sustainable operations.     

关于数论函数方程δ（x^2＋y）＋δ（x＋y^2）=2ψ（x^3＋y^3）

对于正整数k，设δ（k）和ψ（k）分别是k的约数和函数和Dedekind函数．该文证明了：方程仅有正整数解（x,y）=（1，1）．