A multimethod assessment of personal space development in female and male,black and white children

In order to obtain evidence of the effects of demographic parameters and measurement techniques on personal space, several different assessments were used to determine the impact of subject age, race, and sex on interpersonal distancing. Thirteen different variables representing stimulation, paper-and-pencil, and behavioral techniques indicated that as age increased, personal space requirements decreased, particularly for whites. Blacks as compared to whites required less space at age 7, and mixed-sex dyads tended to require more space than same-sex dyads. The results thus indicate that while some previous findings appear to be measurement method specific, others show intermethod consistency.     

A Flexible Evaluative Framework for Order Picking Systems

This paper develops a novel framework to evaluate the integral performance of order picking systems with different combinations of storage and order picking policies. The warehousing literature on order picking mostly considers minimizing either elapsed time or distance as the sole objective, whereas warehouse managers in a supply chain have to look beyond single‐dimensional performance and consider trade‐offs among different criteria. Thus managers still need a unified and efficient framework to select a portfolio of appropriate order picking policies from a multi‐criteria and contextual perspective. Our framework—combining data envelopment analysis, ranking and selection, and multiple comparisons—provides an efficient methodology to simultaneously analyze several interrelated problems in order picking systems with multiple performance attributes, such as service levels and operational costs. We demonstrate our approach through comprehensive evaluations of order picking policies in three low‐level, picker‐to‐parts rectangular warehouses facing demand variations.     

Delta Method,Moment Convergence,and Inference

Statistics, as functions of the observations, are usually given by well-behaved functions. This fact is used to obtain limit distributions for statistics whose components are given by asymptotically linear functions. These results are then extended to the moments of distributions, covariance matrices and confidence regions for parameters of interest. These regions may be used to test, through duality, hypothesis on these parameters. A theoretical application is presented.     

Generalized Jackknife-Based Estimators for Univariate Extreme-Value Modeling

In this article, we revisit the importance of the generalized jackknife in the construction of reliable semi-parametric estimates of some parameters of extreme or even rare events. The generalized jackknife statistic is applied to a minimum-variance reduced-bias estimator of a positive extreme value index—a primary parameter in statistics of extremes. A couple of refinements are proposed and a simulation study shows that these are able to achieve a lower mean square error. A real data illustration is also provided.     

A monte carlo investigation of a statistic for a bivariate missing data problem

Testing the equal means hypothesis of a bivariate normal distribution with homoscedastic varlates when the data are incomplete is considered. If the correlational parameter, ρ, is known, the well-known theory of the general linear model is easily employed to construct the likelihood ratio test for the two sided alternative. A statistic, T, for the case of ρ unknown is proposed by direct analogy to the likelihood ratio statistic when ρ is known. The null and nonnull distribution of T is investigated by Monte Carlo techniques. It is concluded that T may be compared to the conventional t distribution for testing the null hypothesis and that this procedure results in a substantial increase in power-efficiency over the procedure based on the paired t test which ignores the incomplete data. A Monte Carlo comparison to two statistics proposed by Lin and Stivers (1974) suggests that the test based on T is more conservative than either of their statistics.     

On sufficient conditions for the strong consistency of least-squares estimates

The strong consistency of the least-squares estimates in regression models is obtained when the errors are i.i.d. with absolute moment of order r, 0<r? 2. The assumptions presented for the random error sequence will permit us to obtain improvements of the conditions on the regressors in order to obtain the strong consistency of the least-squares estimates in linear and nonlinear regression models.     

Strong consistency of least squares estimates with i.i.d. errors with mean values not necessarily defined

We establish strong consistency of the least squares estimates in multiple regression models discarding the usual assumption of the errors having null mean value. Thus, we required them to be i.i.d. with absolute moment of order r, 0<r<2, and null mean value when r>1. Only moderately restrictive conditions are imposed on the model matrix. In our treatment, we use an extension of the Marcinkiewicz–Zygmund strong law to overcome the errors mean value not being defined. In this way, we get a unified treatment for the case of i.i.d. errors extending the results of some previous papers.     

Consideration of the Aerosol Transmission for COVID-19 and Public Health

This article analyzes the available evidence to address airborne, aerosol transmission of the SARS-CoV-2. We review and present three lines of evidence: case reports of transmission for asymptomatic individuals in association with studies that show that normal breathing and talking produce predominantly small droplets of the size that are subject to aerosol transport; limited empirical data that have recorded aerosolized SARS-CoV-2 particles that remain suspended in the air for hours and are subject to transport over distances including outside of rooms and intrabuilding, and the broader literature that further supports the importance of aerosol transmission of infectious diseases. The weight of the available evidence warrants immediate attention to address the significance of aerosols and implications for public health protection.     

Creating Organisational Strength from Operationalising Restrictions: Welfare Non-profit Organisations in the Russian Federation

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - The work of non-profit organisations (NPOs) in non-democratic country contexts tends to be judged on their contribution to...