Linguistic instrumentalism and national language policy in Mainland China’s state print media coverage of the Protecting Cantonese Movement

This article examines the Chinese government’s use of the print media to justify the national language policy and address individuals’ concerns about the vitality of regional varieties of the Chinese language (i.e., Cantonese) in its coverage of the Protecting Cantonese Movement (July 2010) in Guangzhou. The analysis revealed that the Chinese government adopted a relatively reconciliatory response to the Movement, which apparently contested the relevant language policy. However, the media texts maintained the national policy of promoting Putonghua as inviolable, whereas they assigned Cantonese the role of the carrier of cultural tradition and stressed that the rise or fall of particular regional language depended on regional socioeconomic developments. Such media discussions showed that the state carefully managed relevant discussions about the vitality of regional Chinese varieties within the discursive space defined by legalistic, cultural, and socioeconomic development discourses. These discursive boundaries reflect the dominance of linguistic instrumentalism in the Chinese government’s language policymaking.     

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.     

Comparison of methods for analyzing binary repeated measures data: A simulation-based study (comparison of methods for binary repeated measures)

In this study, some methods suggested for binary repeated measures, namely, Weighted Least Squares (WLS), Generalized Estimating Equations (GEE), and Generalized Linear Mixed Models (GLMM) are compared with respect to power, type 1 error, and properties of estimates. The results indicate that with adequate sample size, no missing data, the only covariate being time effect, and a relatively limited number of time points, the WLS method performs well. The GEE approach performs well only for large sample sizes. The GLMM method is satisfactory with respect to type I error, but its estimates have poorer properties than the other methods.     

Minimum variance unbiased estimation of stress–strength reliability under bivariate normal and its comparisons

In many industrial and natural phenomena, we need the probability that a component is smaller than the other component. Under a stress–strength model, this is reliability of an item. Under independent setup, there are different approaches for the estimation of such reliability. Here, estimation is considered under the dependent case. Under bi-variate setup uniformly minimum variance unbiased estimator is obtained. Also comparison with available estimator based on Maximum Likelihood Estimate (MLE) is done through Mean Square Error (MSE) and bias. Also these are compared by computing L₁ distance between their distribution functions. From this idea and numerical computations, UMVUE appears to be good.     

Variable selection for semiparametric proportional hazards model under progressive Type-II censoring

Variable selection is an effective methodology for dealing with models with numerous covariates. We consider the methods of variable selection for semiparametric Cox proportional hazards model under the progressive Type-II censoring scheme. The Cox proportional hazards model is used to model the influence coefficients of the environmental covariates. By applying Breslow’s “least information” idea, we obtain a profile likelihood function to estimate the coefficients. Lasso-type penalized profile likelihood estimation as well as stepwise variable selection method are explored as means to find the important covariates. Numerical simulations are conducted and Veteran’s Administration Lung Cancer data are exploited to evaluate the performance of the proposed method.     

Designing a multiple state repetitive group sampling plan based on the coefficient of variation

A multiple state repetitive group sampling (MSRGS) plan is developed on the basis of the coefficient of variation (CV) of the quality characteristic which follows a normal distribution with unknown mean and variance. The optimal plan parameters of the proposed plan are solved by a nonlinear optimization model, which satisfies the given producer's risk and consumer's risk at the same time and minimizes the average sample number required for inspection. The advantages of the proposed MSRGS plan over the existing sampling plans are discussed. Finally an example is given to illustrate the proposed plan.     

Statistical inference for the Gompertz distribution based on Type-II progressively hybrid censored data

In this article, the statistical inference for the Gompertz distribution based on Type-II progressively hybrid censored data is discussed. The estimation of the parameters for Gompertz distribution is obtained using maximum likelihood method (MLE) and Bayesian method under three different loss functions. We also proved the existence and uniqueness of the MLE. The one-sample Bayesian prediction intervals are obtained. The work is done for different values of the parameters. We apply the Monto Carlo simulation to compare the proposed methods, also an example is discussed to construct the Prediction intervals.     

Fathers' Investments of Money and Time Across Residential Contexts

Fathers' roles in family life have changed dramatically over the past 50 years. In addition to ongoing breadwinning responsibilities, many fathers are now involved in direct caregiving and engagement with children. Yet there is considerable variation in what fathers do, especially depending on whether they live with or away from their child. In this article, the authors use data from the Fragile Families and Child Wellbeing Study (N = 3,869) to describe how fathers' economic capacities (money) and direct involvement with children (time) are associated over child ages 1 to 9 for resident versus nonresident fathers, net of confounding factors. They found suggestive evidence that money and time investments operate differently across residential contexts: Resident fathers experience a trade‐off between market work and time involved with children. In contrast, nonresident fathers' higher economic capacities are associated with more time involvement, underscoring the greater challenge for such fathers to remain actively involved.