"中国信心":当代中华民族凝聚力的现实解读

"中国信心"不仅仅是一个新闻词汇或政治口号,而是引领当代中国社会发展的民族精神和时代精神的精华.在内涵上,"中国信心"是民族性与时代性的辩证统一,是中国特色社会主义理论体系的重要内容;在本质上,"中国信心"是成就感与使命感的高度结合,是社会主义精神文明建设的时代展示;在功能定位上,"中国信心"是当代中华民族凝聚力增强的鲜明亮点,对提升国家文化软实力具有重要意义.     

Is Gaydar Affected by Attitudes Toward Homosexuality? Confidence,Labeling Bias,and Accuracy

Previous research has largely ignored the relationship between sexual orientation judgement accuracy, confidence, and attitudes toward homosexuality. In an online study, participants (N = 269) judged the sexual orientation of homosexual and heterosexual targets presented via a series of facial photographs. Participants also indicated their confidence in each judgment and completed the Modern Homonegativity Scale (Morrison & Morrison, 2002). We found that (1) homosexual men and heterosexual women were more accurate when judging photographs of women as opposed to photographs of men, and (2) in heterosexual men, negative attitudes toward homosexual men predicted confidence and bias when rating men’s photographs. Findings indicate that homosexual men and heterosexual women are similar in terms of accuracy in judging women’s sexuality. Further, especially in men, homophobia is associated with cognitive biases in labeling other men but does not have a relationship with increased accuracy.     

Seeking Clarity and Confidence in the Divorce Decision-Making Process

There is a well-established literature dedicated to why couples divorce, transitions associated with divorce, and the impact of divorce on families. However, little is known about the divorce decision-making process. We conducted in-depth interviews with individuals who have recently considered divorce (n = 30) and asked specifically about the roles of 2 concepts in their decision-making process: clarity and confidence. Three major themes emerged from the data: (a) Clarity about a decision to divorce or stay married is desired, it fluctuates, and takes time to find; (b) pivotal moments can bring clarity; and (c) confidence (in the final decision) is desired. Clinical implications and directions for future research are discussed.     

Likelihood inference for the component lifetime distribution based on progressively censored parallel systems data

Point and interval estimators for the scale parameter of the component lifetime distribution of a k-component parallel system are obtained when the component lifetimes are assumed to be independently and identically exponentially distributed. We prove that the maximum likelihood estimator of the scale parameter based on progressively Type-II censored system lifetimes is unique and can be obtained by a fixed-point iteration procedure. In particular, we illustrate that the Newton–Raphson method does not converge for any initial value. Furthermore, exact confidence intervals are constructed by a transformation using normalized spacings and other component lifetime distributions including Weibull distribution are discussed.     

Generalized simultaneous confidence regions for regression coefficients and their ratios

This study constructs a simultaneous confidence region for two combinations of coefficients of linear models and their ratios based on the concept of generalized pivotal quantities. Many biological studies, such as those on genetics, assessment of drug effectiveness, and health economics, are interested in a comparison of several dose groups with a placebo group and the group ratios. The Bonferroni correction and the plug-in method based on the multivariate-t distribution have been proposed for the simultaneous region estimation. However, the two methods are asymptotic procedures, and their performance in finite sample sizes has not been thoroughly investigated. Based on the concept of generalized pivotal quantity, we propose a Bonferroni correction procedure and a generalized variable (GV) procedure to construct the simultaneous confidence regions. To address a genetic concern of the dominance ratio, we conduct a simulation study to empirically investigate the probability coverage and expected length of the methods for various combinations of sample sizes and values of the dominance ratio. The simulation results demonstrate that the simultaneous confidence region based on the GV procedure provides sufficient coverage probability and reasonable expected length. Thus, it can be recommended in practice. Numerical examples using published data sets illustrate the proposed methods.     

Estimation of P{X < Y} for geometric—exponential model based on complete and censored samples

This article deals with the estimation of R = P{X < Y}, where X and Y are independent random variables from geometric and exponential distribution, respectively. For complete samples, the MLE of R, its asymptotic distribution, and confidence interval based on it are obtained. The procedure for deriving bootstrap-p confidence interval is presented. The UMVUE of R and UMVUE of its variance are derived. The Bayes estimator of R is investigated and its Lindley's approximation is obtained. A simulation study is performed in order to compare these estimators. Finally, all point estimators for right censored sample from the exponential distribution, are obtained.     

Statistical analysis of dependent competing risks model in accelerated life testing under progressively hybrid censoring using copula function

This article considers statistical analysis of dependent competing risks model from Weibull distribution in accelerated life testing, in which copula function is used to examine the dependence structure between competing failure modes. We derive the maximum likelihood estimates, the approximate, and Bootstrap confidence intervals of the parameters. The effects of different dependence structures on the estimates of parameters are investigated. The simulation is given to compare the performance of the estimates when the competing failure modes are dependent with those when the failure modes are independent. Finally, one dataset was used for illustrative purpose in conclusion.     

Simultaneous decomposition of the variance by sources and subgroups – new insights

There are two types of decompositions: of linear combinations of random variables into contributions of individual variables (sources) and associations between them, and of populations into contributions of their subpopulations. Simultaneous treatment of the two types is called for, which takes into account the correlations between sources within subpopulations and between subpopulation means. The expected values of the subcomponents are derived and their sensitivity to correlations among sources within groups and among source group means is conducted. An example is provided, in which the correlations contribute 20--25% to total variability. This additional information is hidden when decompositions are not simultaneous.     

A new confidence interval in measurement error model with the reliability ratio known

For the slope parameter of the measurement error model with the reliability ratio known, this article constructs a fiducial generalized confidence interval (FGCI) which is proved to have correct asymptotic coverage. Simulation results demonstrate that the FGCI often outperforms the existing intervals in terms of empirical coverage probability, average interval length, and false parameter coverage rate. Two examples are also provided to illustrate our approach.     

The performance of model averaged tail area confidence intervals

We investigate the exact coverage and expected length properties of the model averaged tail area (MATA) confidence interval proposed by Turek and Fletcher, CSDA, 2012, in the context of two nested, normal linear regression models. The simpler model is obtained by applying a single linear constraint on the regression parameter vector of the full model. For given length of response vector and nominal coverage of the MATA confidence interval, we consider all possible models of this type and all possible true parameter values, together with a wide class of design matrices and parameters of interest. Our results show that, while not ideal, MATA confidence intervals perform surprisingly well in our regression scenario, provided that we use the minimum weight within the class of weights that we consider on the simpler model.