A Path Analytic Model of a Theory of Quality Management Underlying the Deming Management Method: Preliminary Empirical Findings*

Despite the impact that Deming and his 14 Points have had on the practice of quality management, empirical support for the effectiveness of the Deming Management Method has not advanced beyond the presentation of anecdotal, case-study evidence. In part, this is because theory to guide the conduct of empirical research has not been available. Only recently has such a theory of quality management to describe and explain the effectiveness of the Deming Management Method been articulated in the literature. This paper continues the journey of theory development; it reports the results of an exploratory empirical analysis of an articulated theory of quality management underlying the Deming Management Method. The constructs in the proposed theory are operationalized using measurement statements developed by the World-Class Manufacturing research project team at the University of Minnesota and Iowa State University. Path analysis is applied to the World-Class Manufacturing project data to explore the empirical strength of relationships advanced in the theory. The path analytic results provide support for several of the proposed relationships in the theory, and more importantly, suggest a number of new relationships which have not heretofore been proposed.     

Sensitivity Analysis in Linear Programming Models with Common Inputs

The importance of sensitivity analysis information in linear programming has been stressed in the management science literature for some time. Indeed, Gal [3] has devoted an entire text to just this issue. Linear programs with common inputs (cost coefficients or right-hand-side values) present a problem in that classical sensitivity analysis does not allow for the simultaneous changes required to determine the sensitivity of these models to common inputs. We first survey the approaches previously developed for simultaneous-change sensitivity analysis and cast them in the framework of the special common input case. These general techniques are compared to a simple aggregate variable technique that has not received attention in the literature.     

Kernel density estimation under negative superadditive dependence and its application for real data

In this paper, the kernel density estimator for negatively superadditive dependent random variables is studied. The exponential inequalities and the exponential rate for the kernel estimator of density function with a uniform version, over compact sets are investigated. Also, the optimal bandwidth rate of the estimator is obtained using mean integrated squared error. The results are generalized and used to improve the ones obtained for the case of associated sequences. As an application, FGM sequences that fulfil our assumptions are investigated. Also, the convergence rate of the kernel density estimator is illustrated via a simulation study. Moreover, a real data analysis is presented.     

On Bartlett correction of empirical likelihood for regularly spaced spatial data

Bartlett correction constitutes one of the attractive features of empirical likelihood because it enables the construction of confidence regions for parameters with improved coverage probabilities. We study the Bartlett correction of spatial frequency domain empirical likelihood (SFDEL) based on general spectral estimating functions for regularly spaced spatial data. This general formulation can be applied to testing and estimation problems in spatial analysis, for example testing covariance isotropy, testing covariance separability as well as estimating the parameters of spatial covariance models. We show that the SFDEL is Bartlett correctable. In particular, the improvement in coverage accuracies of the Bartlett‐corrected confidence regions depends on the underlying spatial structures. The Canadian Journal of Statistics 47: 455–472; 2019 © 2019 Statistical Society of Canada     

A new aging concept derived from the increasing convex ordering

In this paper, a comparison between the life distribution of a new unit with that of a used unit in the increasing convex order is made leading to a new class of life distributions which we call “new better than used in convex ordering of second order”. This class includes as subclasses the NBU and the NBUC and is a subclass of the NBUCA class. Preservation properties under convolution, random maxima, mixing and formation of coherent structures are established. Stochastic comparisons of the excess lifetime when the inter-arrival times belong to the NBUC(2) class are developed. Some applications of Poisson shock models and a test of exponentiality against NBUC(2) alternative are presented.     

Special issue dedicated to Odd O. Aalen

Lifetime Data Analysis -     

Socioeconomic Resource Environments in Biological and Alternative Family Care and Children's Cognitive Performance*

We examined social and economic resources in the environments of children involved with child protective services and their associations with children's cognitive performance. We used a national dataset of child protection investigations (children aged 6–16 at Wave 1). Using latent class analysis, we constructed profiles of the financial resources, parental education and employment, and family structure and size. We then examined within‐ and across‐time associations between resource environment profiles and children's math and reading scores and tested whether associations differed by family care type. Our latent class analysis identified four distinct family resource environments: educated middle class, single earner, large working class, and severely disadvantaged. Family resource environment profiles predicted current cognitive performance and changes in performance over time, but associations were more consistent for children in biological family care. Children who remain in home following maltreatment allegations may benefit from services that target social as well as economic resources.     

The Role of Self-Conscious Emotions in the Sexual Health of Gay and Bisexual Men: Psychometric Properties and Theoretical Validation of the Sexual Shame and Pride Scale

Researchers have theorized about the role of sexual shame as a mechanism through which sexual minority stress manifests into mental health difficulties, such as sexual compulsivity for gay and bisexual men (GBM), and about the resilience-promoting effects of sexual pride. However, no validated measures to date have directly tapped into these constructs rather than using proxies for them, such as internalized homonegativity. We developed the Sexual Shame and Pride Scale (SSPS) and conducted a psychometric evaluation of it using a sample of 260 highly sexually active GBM. The scale had the expected structure in factor analysis and showed evidence of internal consistency and test–retest reliability. Correlational analyses demonstrated the convergent validity of sexual shame and sexual pride with relevant constructs. Regression analyses demonstrated the predictive validity of sexual shame in relation to sexual compulsivity, accounting for unique variability even after adjusting for previously demonstrated etiological factors, and the predictive validity of both shame and pride, which interacted to consistently predict four sexual behavior outcomes. Findings suggest the SSPS is a psychometrically valid and reliable measure that may be useful in future empirical work and highlight preliminary evidence for the role of these constructs in the sexual health of GBM.