After the Honeymoon: The Evolution of Problem Issues in Utah LDS Marriages

The main objective of this study was to extend previous research in the area of longitudinal marital satisfaction by examining how marital issues, including decision-making, activities, affection, conflict, financial matters, stability, and values, changed over the first 5 years of marriage for 242 Utah, Latter-Day-Saint individuals. In addition, this study examined whether change occurs differently for husbands versus wives and for at-risk individuals versus non-risk individuals. The results showed that four marital issues worsened over time (activities, affection, conflict, and stability). Two of the six subscales (activities and affection) were found to differ significantly by gender. In addition, four subscales were significantly different for at-risk couples when compared with non-risk couples (decision-making, activities, conflict, and stability). Limitations and recommendations are discussed.     

Advancing Research on LGBTQ Microaggressions: A Psychometric Scoping Review of Measures

ABSTRACT

Understanding the nature and consequences of LGBTQ microaggressions is critical to fostering equity and wellbeing among sexual and gender minorities. Yet little guidance is available for researchers seeking psychometrically robust measures of subtle LGBTQ slights, invalidations, and insults. To address this gap, we conducted a scoping review of multi-item quantitative measures that included at least one question addressing LGBTQ microaggressions. This article reports the study characteristics and psychometric properties of 27 original measures we identified and their subsequent adaptations. The article concludes with an assessment of strengths and limitations of LGBTQ microaggression measurement, highlighting aspects of measurement innovation on which future researchers can build. As microaggressions remain a powerful and underexplored mechanism of sexual and gender minority oppression, this review will help to both advance methodological quality in this critical research area and enhance our understanding of how microaggressions manifest in the lives of LGBTQ individuals.     

Optimal ordering and pricing decisions for a target oriented newsvendor

This paper is the first to study pricing and target oriented decision making together in the newsvendor model. Specifically, this paper studies a newsvendor who decides on order quantity and selling price to maximize the probability of achieving both profit and revenue targets simultaneously. First, it is shown that the probability of a newsvendor achieving both targets depends critically on the relative magnitudes of the profit margin and the ratio between the profit target and the revenue target. Second, the closed-form expressions of the optimal order quantity, the optimal selling price, and the maximal profit and revenue probability are obtained. It is shown that if the product has greater price elasticity, the best strategy is always to price lower and order more.     

Beyond products: new strategic imperatives for developing competencies in dynamic environments

Strategy research has often taken a product-centered perspective. When firms compete in environments characterized by accelerating product life cycles, mass customization, and technological discontinuities, a product-centered perspective on strategy may help explain a firm’s current competitive advantage. However, this perspective adds little guidance in making strategies that create competitive advantage in the future. In this paper, we present a perspective in which dynamic environments require firms to focus on (1) building market-driven, technological, and integration competencies, not a stream of product improvements, and (2) decoupling these competencies from current products in order to create and exploit new opportunities. We discuss the perspective of products as a temporary integration of market and technology trajectories. Research propositions are presented and future implications are discussed.     

The mediating role of work-to-family conflict in the relationship between shiftwork and depression

Abstract

With significant segments of the working population involved in shiftwork, there is the possibility of serious health outcomes. There are two possible pathways to ill health. In the biological pathway the body's circadian rhythms are affected, leading to physiological disturbances and the inability to cope. By contrast, the aim of this study is to elucidate a social pathway by which shiftwork may lead to mental ill health. It examines the mediating influence of work-to-family conflict in the association between shiftwork and depression. Gender differences are also investigated. The sample included 2,931 Canadian respondents with a spouse and at least one child living at home. Close to 28% of respondents were involved in some form of shiftwork. Structural equation modelling supported partial mediation through work-to-family conflict. Further analyses found that mediation was supported in sub-samples of male and female respondents. The results, however, suggest that the experience of shiftwork is quite similar for men and women as no significant differences were found between mediating models. Overall, the findings support the social explanation of the effect of shiftwork on mental health, but they do not rule out other social or biological pathways.     

Estimation and Confidence Regions for Parameter Sets in Econometric Models1

This paper develops a framework for performing estimation and inference in econometric models with partial identification, focusing particularly on models characterized by moment inequalities and equalities. Applications of this framework include the analysis of game‐theoretic models, revealed preference restrictions, regressions with missing and corrupted data, auction models, structural quantile regressions, and asset pricing models. Specifically, we provide estimators and confidence regions for the set of minimizers Θ_I of an econometric criterion function Q(θ). In applications, the criterion function embodies testable restrictions on economic models. A parameter value θthat describes an economic model satisfies these restrictions if Q(θ) attains its minimum at this value. Interest therefore focuses on the set of minimizers, called the identified set. We use the inversion of the sample analog, Q_n(θ), of the population criterion, Q(θ), to construct estimators and confidence regions for the identified set, and develop consistency, rates of convergence, and inference results for these estimators and regions. To derive these results, we develop methods for analyzing the asymptotic properties of sample criterion functions under set identification.     

Parameterization and inference for nonparametric regression problems

We consider local likelihood or local estimating equations, in which a multivariate function () is estimated but a derived function () of () is of interest. In many applications, when most naturally formulated the derived function is a non-linear function of (). In trying to understand whether the derived non-linear function is constant or linear, a problem arises with this approach: when the function is actually constant or linear, the expectation of the function estimate need not be constant or linear, at least to second order. In such circumstances, the simplest standard methods in nonparametric regression for testing whether a function is constant or linear cannot be applied. We develop a simple general solution which is applicable to nonparametric regression, varying-coefficient models, nonparametric generalized linear models, etc. We show that, in local linear kernel regression, inference about the derived function () is facilitated without a loss of power by reparameterization so that () is itself a component of (). Our approach is in contrast with the standard practice of choosing () for convenience and allowing ()> to be a non-linear function of (). The methods are applied to an important data set in nutritional epidemiology.     

Use of an empirical probability generating function for testing a Poisson model

We present a test of the fit to a Poisson model based on the empirical probability generating function (epgf). We derive the limiting distribution of the test under the Poisson hypothesis and show that a rescaling of it is approximately independent of the mean parameter in the Poisson distribution. When inspected under a simulation study over a range of alternative distributions, we find that this test shows reasonable behaviour compared to other goodness-of-fit tests like the Poisson index of dispersion and smooth test applied to the Poisson model. These results illustrate that epgf-based methods for anlyzing count data are promising.