Marginal zero-inflated regression models for count data

Data sets with excess zeroes are frequently analyzed in many disciplines. A common framework used to analyze such data is the zero-inflated (ZI) regression model. It mixes a degenerate distribution with point mass at zero with a non-degenerate distribution. The estimates from ZI models quantify the effects of covariates on the means of latent random variables, which are often not the quantities of primary interest. Recently, marginal zero-inflated Poisson (MZIP; Long et al. [A marginalized zero-inflated Poisson regression model with overall exposure effects. Stat. Med. 33 (2014), pp. 5151–5165]) and negative binomial (MZINB; Preisser et al., 2016) models have been introduced that model the mean response directly. These models yield covariate effects that have simple interpretations that are, for many applications, more appealing than those available from ZI regression. This paper outlines a general framework for marginal zero-inflated models where the latent distribution is a member of the exponential dispersion family, focusing on common distributions for count data. In particular, our discussion includes the marginal zero-inflated binomial (MZIB) model, which has not been discussed previously. The details of maximum likelihood estimation via the EM algorithm are presented and the properties of the estimators as well as Wald and likelihood ratio-based inference are examined via simulation. Two examples presented illustrate the advantages of MZIP, MZINB, and MZIB models for practical data analysis.     

Toward a More Complex View of Career Exploration

This article examines the concept of career exploration in adult populations. In contrast to the prevailing positive view of career exploration, the authors present a more complex and balanced perspective of this process, addressing some of the barriers to career exploration and the applicability of this concept to different populations. They examine differences between voluntary exploration and forced or chance exploration, discuss how relationships may be barriers to exploration, consider various outcomes of career explorations, and call for a more holistic view of the individual in career counseling.     

The Effects of Multitasking on Operations Scheduling

This study considers a typical scheduling environment that is influenced by the behavioral phenomenon of multitasking. Under multitasking, the processing of a selected job suffers from interruption by other jobs that are available but unfinished. This situation arises in a wide variety of applications; for example, administration, manufacturing, and process and project management. Several classical solution methods for scheduling problems no longer apply in the presence of multitasking. The solvability of any scheduling problem under multitasking is no easier than that of the corresponding classical problem. We develop optimal algorithms for some fundamental and practical single machine scheduling problems with multitasking. For other problems, we show that they are computationally intractable, even though in some cases the corresponding problem in classical scheduling is efficiently solvable. We also study the cost increase and value gained due to multitasking. This analysis informs companies about how much it would be worthwhile to invest in measures to reduce or encourage multitasking.     

Importance of interpolation when constructing double-bootstrap confidence intervals

We show that, in the context of double-bootstrap confidence intervals, linear interpolation at the second level of the double bootstrap can reduce the simulation error component of coverage error by an order of magnitude. Intervals that are indistinguishable in terms of coverage error with theoretical, infinite simulation, double-bootstrap confidence intervals may be obtained at substantially less computational expense than by using the standard Monte Carlo approximation method. The intervals retain the simplicity of uniform bootstrap sampling and require no special analysis or computational techniques. Interpolation at the first level of the double bootstrap is shown to have a relatively minor effect on the simulation error.     

Confidence intervals for secondary parameters following a sequential test

In sequential studies, formal interim analyses are usually restricted to a consideration of a single null hypothesis concerning a single parameter of interest. Valid frequentist methods of hypothesis testing and of point and interval estimation for the primary parameter have already been devised for use at the end of such a study. However, the completed data set may warrant a more detailed analysis, involving the estimation of parameters corresponding to effects that were not used to determine when to stop, and yet correlated with those that were. This paper describes methods for setting confidence intervals for secondary parameters in a way which provides the correct coverage probability in repeated frequentist realizations of the sequential design used. The method assumes that information accumulates on the primary and secondary parameters at proportional rates. This requirement will be valid in many potential applications, but only in limited situations in survival analysis.     

The Informal Sector: A Review and Agenda for Management Research

Despite its connotations of non‐compliance, illegality, social exploitation and marginality, the informal sector is a substantial contributor to economic life in developing countries and, increasingly, in more technologically advanced activities. Its prevalence in developed economies has also become more widely recognized. In light of its significance, this paper reviews research on the informal sector from a management and organization scholarship perspective, rather than from an entrepreneurship view, as has been the focus until now. It sets out the atypical management practices that are inherent in the sector, explores the under‐researched relationship between formal and informal firms, and highlights definitional, conceptual and other limitations in extant research. As a step in resolving these issues, the authors present a conceptual model of formality and informality in a three‐dimensional framework that highlights an organizational infrastructure dimension, a view of firms operating along a continuum, and a multi‐level analytical context. Building on this, the authors detail opportunities for enhanced appreciation of in situ management and organizational practices in the informal sector and outline tools for pursuing a management and organization scholarship agenda. Overall, the authors argue that management scholarship has great potential to improve understanding of the informal sector, and that the informal sector provides opportunities to advance management theory, research and practice.     

Mistreatment and self-reported emotional symptoms: results from the National Elder Mistreatment Study

Many community-residing older adults in the United States report past year mistreatment; however, little is known about mental health correlates of abuse. This study investigated whether a recent history of emotional, physical, or sexual abuse is associated with self-reported emotional symptoms (e.g., anxiety, depression) among a representative sample of older adults. Results demonstrated that each abuse type increased likelihood of reporting emotional symptoms; when other known correlates were controlled, only emotional abuse remained a significant predictor. Additional study of mistreatment-related correlates of depression and anxiety is needed, with a focus on the often overlooked category of emotional mistreatment.