Variance-balanced row–column designs involving diallel crosses incorporating specific combining abilities for comparing test lines with a control line

In this paper, the problem of comparing t test lines with a control line under a row–column setup in complete diallel cross experiment is investigated when specific combining ability (sca) effect is included in the model. Three classes of Mating-Environmental Row–Column (MERC) designs have been obtained which are variance balanced for estimating the contrasts pertaining to general combining ability (gca) effects free from sca effects.     

Heteroskedasticity–robust tests with minimum size distortion

Asymptotically valid inference in linear regression models is easily achieved under mild conditions using the well-known Eicker–White heteroskedasticity–robust covariance matrix estimator or one of its variant. In finite sample however, such inferences can suffer from substantial size distortion. Indeed, it is well established in the literature that the finite sample accuracy of a test may depend on which variant of the Eicker–White estimator is used, on the underlying data generating process (DGP) and on the desired level of the test.

This paper develops a new variant of the Eicker–White estimator which explicitly aims to minimize the finite sample null error in rejection probability (ERP) of the test. This is made possible by selecting the transformation of the squared residuals which results in the smallest possible ERP through a numerical algorithm based on the wild bootstrap. Monte Carlo evidence indicates that this new procedure achieves a level of robustness to the DGP, sample size and nominal testing level unequaled by any other Eicker–White estimator based asymptotic test.     

Exponentiated power Lindley–Poisson distribution: Properties and applications

A new four-parameter distribution called the exponentiated power Lindley–Poisson distribution which is an extension of the power Lindley and Lindley–Poisson distributions is introduced. Statistical properties of the distribution including the shapes of the density and hazard functions, moments, entropy measures, and distribution of order statistics are given. Maximum likelihood estimation technique is used to estimate the parameters. A simulation study is conducted to examine the bias, mean square error of the maximum likelihood estimators, and width of the confidence interval for each parameter. Finally, applications to real data sets are presented to illustrate the usefulness of the proposed distribution.     

A note on generating correlated matched-pair binary data through conditional linear family

Generating correlated binary data with specified marginal probabilities and correlation structure is often needed and useful in simulation studies to investigate the finite sample performance of statistical methods. Conditional linear family provides a powerful and flexible tool to generate correlated matched-pair binary data including the physician–patients and clustered match-pair data. To ensure the validity of the data generation process, constraints for parameters of the conditional linear family are needed. For the correlated matched-pair binary data with an exchangeable-type correlation structure, we derive the explicit expressions to check these constraints and it provides an efficient and convenient computational tool in validating the data generation process. The results are applied to check the constraints for two typical correlated matched-pair binary data.     

Detecting influential observations in Watson data

A method for detecting outliers in axial data has been proposed by Best and Fisher (1986 Best, D.J., Fisher, N.I. (1986). Goodness-of-fit and discordancy tests for samples from the Watson distribution on the sphere. Aust. J. Stat. 28:13–31.[Crossref] , [Google Scholar]). For extending that work, we propose four new methods. Two of them are suitable for outlier detection and they depend on the classic geodesic distance and a modified version of this distance. The other two procedures, which are designed for influential observation detection, are based on the Kullback–Leibler and Cook’s distances. Some simulation experiments are performed to compare all considered methods. Detection and error rates are used as comparison criteria. Numerical results provide evidence in favor of the KL distance.     

Not every Gibbs sampler is a special case of the Metropolis–Hastings algorithm

It is commonly asserted that the Gibbs sampler is a special case of the Metropolis–Hastings (MH) algorithm. While this statement is true for certain Gibbs samplers, it is not true in general for the version that is taught and used most often, namely, the deterministic scan Gibbs sampler. In this note, I prove that that there exist deterministic scan Gibbs samplers that do not exhibit detailed balance and hence cannot be considered MH samplers. The nuances of various Gibbs sampling schemes are discussed.     

Pseudo maximum-likelihood estimation of the univariate GARCH (1,1) and asymptotic properties

One provides in this paper the pseudo-likelihood estimator (PMLE) and asymptotic theory for the GARCH (1,1) process. Strong consistency of the pseudo-maximum-likelihood estimator (MLE) is established by appealing to conditions given in Jeantheau (1998) concerning the existence of a stationary and ergodic solution to the multivariate GARCH (p, q) process. One proves the asymptotic normality of the PMLE by appealing to martingales' techniques.     

The Stochastic Volatility in Mean Model With Time-Varying Parameters: An Application to Inflation Modeling

This article generalizes the popular stochastic volatility in mean model to allow for time-varying parameters in the conditional mean. The estimation of this extension is nontrival since the volatility appears in both the conditional mean and the conditional variance, and its coefficient in the former is time-varying. We develop an efficient Markov chain Monte Carlo algorithm based on band and sparse matrix algorithms instead of the Kalman filter to estimate this more general variant. The methodology is illustrated with an application that involves U.S., U.K., and Germany inflation. The estimation results show substantial time-variation in the coefficient associated with the volatility, highlighting the empirical relevance of the proposed extension. Moreover, in a pseudo out-of-sample forecasting exercise, the proposed variant also forecasts better than various standard benchmarks.     

Employee work-to-family role boundary management in the family business

Family-owned organizations present a unique opportunity to study work-to-family boundary management. Boundary theory suggests that work-to-family boundary dynamics may be different in family businesses, and that family businesses are not a neutral ground for individual employees’ segmentation preferences. The present study draws on the sociocognitive processes underlying boundary theory to explain how the family business context may affect family and nonfamily employees’ work-to-family role management differently. The study examines the work-to-family role boundary configurations of 149 family and non-family employees in family businesses. Results suggest that family employee status buffers against undesirable effects of segmentation preferences in the family business context. For family employees, segmentation preferences were associated with lower work-to-family conflict and unassociated with turnover intentions. For non-family employees, segmentation preferences were associated with higher work-to-family conflict and turnover intentions. Implications for work–family theory and family business successorship and work–family policy are discussed.     

The case for humane education in social work education

Humane education focuses on the interconnectedness between human rights, environmental sustainability, and animal protection, and started in the United States in 1996 through the Institute of Humane Education. While social work and social work education has emphasized human rights, the ecological, person-in-environment perspectives need to be expanded to include environmental preservation and animal welfare considering the numerous negative consequences on the global ecosystems. This article makes the case that humane education is an interdisciplinary link for helping social work educators expand their definitions of environmental justice and human–animal relationships so that student ecological consciousness includes the welfare of humans, nonhumans, and the broader ecosystem in their pursuit of change. It offers practical suggestions for opportunities to do this in the social work curriculum.