A permutation approach for testing heterogeneity in two-sample categorical variables

In many sciences researchers often meet the problem of establishing if the distribution of a categorical variable is more concentrated, or less heterogeneous, in population P ₁ than in population P ₂. An approximate nonparametric solution to this problem is discussed within the permutation context. Such a solution has similarities to that of testing for stochastic dominance, that is, of testing under order restrictions, for ordered categorical variables. Main properties of given solution and a Monte Carlo simulation in order to evaluate its degree of approximation and its power behaviour are examined. Two application examples are also discussed.     

Public relations strategies for creating mass media content: A case study of the National Basketball Association

In the relationship among public relations, mass media, and the audience, it is often the mass media who are deemed the power brokers in their ability to potentially influence an audience. The agenda-setting theoretical framework operates from the perspective of the mass media having the power to transfer the salience of an issue to the public. Perhaps, however, to much power is granted to the mass media without the consideration of the processes by which mass media content is selected and framed. This raises the question: who sets the public agenda? Public relations practitioners have the ability to assist the production of mass media content through various proactive public relations strategies that are designed to promote and present the organization they represent in the most positive manner. A case study of the National Basketball Association (NBA) reveals several public relations and promotional strategies, which indicate that much of the creation of NBA related mass media content is directed by the NBA itself.John A. Fortunato is an assistant professor of Communication at Saint Peter’s College, Jersey City, NJ.     

Neurocognitive Effects in Welders Exposed to Aluminium: An Application of the NPC Test and NPC Ranking Methods

The aim of this study is to investigate the effects of exposure to aluminium on the cognitive sphere in a group of welders. Given the intrinsic complexity of the neurocognitive sphere, three different psychomotor variables were used for its investigation allowing the resulting problem to be naturally modelized into a multivariate framework and solved by a nonparametric combination of permutation tests (NPC test). In order to make the treated and control groups comparable, we also stratified the samples on the basis of a risk index that estimates the combined action of biological age and exposure time. Despite the fact that studies in the literature have reached conflicting results, our study highlights a significant drop in attention and memory performances in individuals exposed to aluminium. Finally, we identify a global criterion that summarises the information on the neurocognitive state by applying the nonparametric combination of dependent rankings method (NPC ranking).     

Understanding a non-causality crisis response: Examining the Florida Panthers response to Hurricane Irma

Much of the crisis response literature focuses on an organization deemed to be responsible for the occurrence of the crisis. For a crisis without a singular organization causality, such as a natural disaster, any organization can proactively initiate actions to address the situation. This article contributes to the understanding of a non-causality crisis response by identifying the capabilities that an organization needs to effectively assist with the response. An organization must possess the requisite resources, have developed key stakeholder relationships, and be driven by its own values and sense of responsibility. A sports team is well-positioned to assist with a non-causality crisis response. A sports team creates a feeling of community identity, has a vast array of resources, and has many critical stakeholder relationships. This article examines the NHL’s Florida Panthers relief efforts in response to Hurricane Irma, a storm that created a complex community crisis with residents in need of essential supplies and assistance.     

Analysis of the lifted weight including height and frequency factors for workers in Colombia

Factors related to the height of the load and the frequency of handling have become a way to predict the acceptable standard weight lifted for workers whose main task is the manual lifting of materials and measuring the conditions is important to determine a maximum weight lifted. This study was conducted to twenty (20) workers between eighteen (18) and forty (40) years old with a minimum six months experience and belonging to the warehouse and packaging area of a dairy products company. Consideration was given to three different heights such as knuckle, shoulder and total height as well as frequencies of 2, 4 and 6 times per minute. Average values for lifted weight were 17.9306 ± 2.37 kg. The conclusions and recommendations included a review of legislation related to Colombian maximum acceptable weight of lifting due to the current law does not match the acceptable weight handled in this research.     

A unified approach to permutation testing for equivalence

Statistical Methods & Applications - The notion of testing for equivalence of two treatments is widely used in clinical trials, pharmaceutical experiments, bioequivalence and quality control....     

Some Elementary Theory of Permutation Tests

In literature, permutation tests are mostly derived by means of heuristic arguments (Edgington and Onghena, 2007 Edgington, E.S., Onghena, P. (2007). Randomization Tests (4th ed.). Boca Raton: Chapman & Hall/CRC.[Crossref] , [Google Scholar]; Good, 2005 Good, P. (2005). Permutation, Parametric, and Bootstrap Tests of Hypotheses (3rd ed.). New York: Springer-Verlag. [Google Scholar]). In this paper, we derive them within the sufficiency and conditionality principles of inference. Most important of their properties are exposed without formal proofs that can be found in the book by Pesarin and Salmaso (2010).     

A review and some new results on permutation testing for multivariate problems

In recent years permutation testing methods have increased both in number of applications and in solving complex multivariate problems. When available permutation tests are essentially of an exact nonparametric nature in a conditional context, where conditioning is on the pooled observed data set which is often a set of sufficient statistics in the null hypothesis. Whereas, the reference null distribution of most parametric tests is only known asymptotically. Thus, for most sample sizes of practical interest, the possible lack of efficiency of permutation solutions may be compensated by the lack of approximation of parametric counterparts. There are many complex multivariate problems, quite common in empirical sciences, which are difficult to solve outside the conditional framework and in particular outside the method of nonparametric combination (NPC) of dependent permutation tests. In this paper we review such a method and its main properties along with some new results in experimental and observational situations (robust testing, multi-sided alternatives and testing for survival functions).     

Conditional tests in a competing risks model

Testing for equality of competing risks based on their cumulative incidence functions (CIFs) or their cause specific hazard rates (CSHRs) has been considered by many authors. The finite sample distributions of the existing test statistics are in general complicated and the use of their asymptotic distributions can lead to conservative tests. In this paper we show how to perform some of these tests using the conditional distributions of their corresponding test statistics instead (conditional on the observed data). The resulting conditional tests are initially developed for the case of k = 2 and are then extended to k > 2 by performing a sequence of two sample tests and by combining several risks into one. A simulation study to compare the powers of several tests based on their conditional and asymptotic distributions shows that using conditional tests leads to a gain in power. A real life example is also discussed to show how to implement such conditional tests.