Inferences on the Means of Two Log-Normal Distributions: A Computational Approach Test

In this article, we propose a novel approach for testing the equality of two log-normal populations using a computational approach test (CAT) that does not require explicit knowledge of the sampling distribution of the test statistic. Simulation studies demonstrate that the proposed approach can perform hypothesis testing with satisfying actual size even at small sample sizes. Overall, it is superior to other existing methods. Also, a CAT is proposed for testing about reliability of two log-normal populations when the means are the same. Simulations show that the actual size of this new approach is close to nominal level and better than the score test. At the end, the proposed methods are illustrated using two examples.     

Do Professionals Take Over? Professionalisation and Membership Influence in Civil Society Organisations

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - While many scholars have postulated the decline of membership influence as an important consequence of the...     

A new long-term survival model with dispersion induced by discrete frailty

Lifetime Data Analysis - Frailty models are generally used to model heterogeneity between the individuals. The distribution of the frailty variable is often assumed to be continuous. However, there...     

On hysteretic vector autoregressive model with applications

This paper proposes a new hysteretic vector autoregressive (HVAR) model in which the regime switching may be delayed when the hysteresis variable lies in a hysteresis zone. We integrate an adapted multivariate Student-t distribution from amending the scale mixtures of normal distributions. This HVAR model allows for a higher degree of flexibility in the degrees of freedom for each time series. We use the proposed model to test for a causal relationship between any two target time series. Using posterior odds ratios, we overcome the limitations of the classical approach to multiple testing. Both simulated and real examples herein help illustrate the suggested methods. We apply the proposed HVAR model to investigate the causal relationship between the quarterly growth rates of gross domestic product of United Kingdom and United States. Moreover, we check the pairwise lagged dependence of daily PM2.5 levels in three districts of Taipei.     

Exploring in Silence: Hearing and Deaf Infants Explore Objects Differently Before Cochlear Implantation

Infant development has rarely been informed by the behavior of infants with sensory differences despite increasing recognition that infant behavior itself creates sensory learning opportunities. The purpose of this study of object exploration was to compare the behavior of hearing and deaf infants, with and without cochlear implants, in order to identify the effects of profound sensorineural hearing loss on infant exploration before cochlear implantation, the behavioral effects of access to auditory feedback after cochlear implantation, and the sensory motivation for exploration behaviors performed by hearing infants as well. The results showed that 9‐month‐old deaf infants explored objects as often as hearing infants but they used systematically different approaches and less variation before compared to after cochlear implantation. Potential associations between these early experiences and later learning are discussed in the context of embodied developmental theory, comparative studies, and research with adults. The data call for increased recognition of the active sensorimotor nature of infant learning and future research that investigates differences in sensorimotor experience as potential mechanisms in later learning and sequential memory development.     

Developing a Rubric for Supervision of Students Counseling LGBTQ Clients

More than 100 pieces of anti-lesbian, gay, bisexual, transgender (LGBT) legislation are active in 2018. In this current political climate of “conscience clause” legislation, counselor educators and supervisors are poised to adopt more holistic practices in assessing and evaluating student and supervisee readiness to work with LGBT queer (Q) clients. The purpose of this article is to present a dispositional framework for assessment and evaluation and introduce the flexibility, integrity, awareness, stability, compassion, and openness (FIASCO) rubric of professional counseling dispositions. Two court cases, Keeton v. Anderson-Wiley and Ward v. Wilbanks, are used as case examples for applying the FIASCO rubric to situations involving LGBTQ clients.     

The matching extension problem in general graphs is co-NP-complete

A simple connected graph G with 2n vertices is said to be k-extendable for an integer k with \(0<k<n\) if G contains a perfect matching and every matching of cardinality k in G is a subset of some perfect matching. Lakhal and Litzler (Inf Process Lett 65(1):11–16, 1998) discovered a polynomial algorithm that decides whether a bipartite graph is k-extendable. For general graphs, however, it has been an open problem whether there exists a polynomial algorithm. The new result presented in this paper is that the extendability problem is co-NP-complete.     

Nested exposure case-control sampling: a sampling scheme to analyze rare time-dependent exposures

For large cohort studies with rare outcomes, the nested case-control design only requires data collection of small subsets of the individuals at risk. These are typically randomly sampled at the observed event times and a weighted, stratified analysis takes over the role of the full cohort analysis. Motivated by observational studies on the impact of hospital-acquired infection on hospital stay outcome, we are interested in situations, where not necessarily the outcome is rare, but time-dependent exposure such as the occurrence of an adverse event or disease progression is. Using the counting process formulation of general nested case-control designs, we propose three sampling schemes where not all commonly observed outcomes need to be included in the analysis. Rather, inclusion probabilities may be time-dependent and may even depend on the past sampling and exposure history. A bootstrap analysis of a full cohort data set from hospital epidemiology allows us to investigate the practical utility of the proposed sampling schemes in comparison to a full cohort analysis and a too simple application of the nested case-control design, if the outcome is not rare.