An Exploration of the Meaning and Consequences of Workaholism

Although much has been written aboutworkaholism, rigorous research andtheoretical development on the topic is in its infancy.We integrate literature from multiple disciplines andoffer a definition of workaholic behavior. We identify three types ofworkaholic behavior patterns: compulsive-dependent,perfectionist, and achievement-oriented workaholism. Apreliminary model is proposed; it identifies potential linkages between each type of workaholismpattern and important outcomes such as performance, joband life satisfaction, and turnover. Specificpropositions for future research are articulated. Weconclude that, depending on the type of workaholicbehavior pattern, workaholism can be good or bad, andits consequences may be experienced or evaluateddifferently by individuals, organizations, and societyat large. Researchers and managers should avoidmaking judgments about the positive or negative effectsof workaholism until more carefully controlled researchhas been published.     

A comparison of approaches for estimating the effect of women's education on the probability of using modern contraceptive methods in Malawi

The aim of this study is to estimate the effect of education on the probability of married Malawian women using modern contraceptive methods by accounting for both observed and unobserved confounders. We conduct a sensitivity analysis and compare the results of naive models with instrumental variable models to account for the potential endogeneity of education. Our findings demonstrate conflicting results between the two modelling approaches. The naive models report smaller education effects on the probability of using modern contraceptive methods compared to instrumental variable models. We also find that by relaxing the functional form assumption on the effect of continuous covariates, using a flexible instrumental variable model, the education's effect follows a positive, nonlinear pattern. This finding is not observed with a classic instrumental variable model.     

Contempt and disgust: the emotions of disrespect

Contempt and disgust share a number of features which distinguish them from other hostile emotions: they both present two distinct facets—a nonmoral facet and a moral one; they both imply a negative evaluation of the dispositional kind as well as disrespect towards the target of the feeling; and they trigger avoidance and exclusion action tendencies. However, while sharing a common core, contempt and disgust are in our view distinct emotions, qualified by different cognitive‐motivational features. Contempt is felt exclusively towards human targets, and implies sense of superiority over them, pessimistic feelings about their possibility of betterment, detachment from them, and avoidance driven by detachment; whereas disgust can be directed at a wide range of possible targets, and implies contamination sensitivity, fear of contamination, and fear‐driven avoidance. The differences between contempt and disgust are related to the different kinds of standard against which the target is evaluated, and the different kinds of disrespect engendered by the negative evaluation.     

OUTCOME UNCERTAINTY,FAN TRAVEL,AND AGGREGATE ATTENDANCE

The uncertainty of outcome hypothesis (UOH) informs economists' understanding of consumer decisions to attend sporting events and team revenue generation. We develop a model of fan behavior based on standard expected utility methods which incorporates fan heterogeneity in terms of decisions to travel to away games and strong preferences for wins. The model reflects aggregate attendance outcomes across local and visiting fans, generates predictions consistent with the UOH, and gives rise to concave league-wide revenue functions. Empirical analysis of game outcomes and attendance at regular season National Basketball association games from 1979 to 2013 supports key predictions of the model. (JEL L83, D12, Z20)     

Revising a Prognostic Index Developed for Classification Purposes: an Application to Gastric Cancer Data

A prognostic index (PI) is usually derived from a regression model as a weighted mean of the covariates, with weights (partial scores) proportional to the parameter estimates. When a PI is applied to patients other than those considered for its development, the issue of assessing its validity on the new case series is crucial. For this purpose, Van Houwelingen (2000) proposed a method of validation by calibration, which limits overfitting by embedding the original model into a new one, so that only a few parameters will have to be estimated. Here we address the problem of PI validation and revision with the above approach when the PI has classification purposes and it represents the linear predictor of a Weibull model, derived from an accelerated failure time parameterization instead of a proportional hazards one, as originally described by Van Houwelingen. We show that the Van Houwelingen method can be applied in a straightforward manner, provided that the parameterization originally used in the PI model is appropriately taken into account. We also show that model validation and revision can be carried out by modifying the cut-off values used for prognostic grouping without affecting the partial scores of the original PI. This procedure can be applied to simplify the clinician's use of an established PI for classification purposes.     

How to Silence One's Conscience: Cognitive Defenses Against the Feeling of Guilt

This work presents an analysis of the feeling of guilt and in particular of the cognitive defenses against it. It shows how the need to avoid or mitigate the feeling, with the suffering implied, affects the perception and judgment of oneself and others. It is in fact claimed that to copy with their guilt people try to alter the appraisal processes implied by the emotion. Once described the main cognitive components of the feeling of guilt, an analysis is offered of the interventions of the cognitive defenses on such components, to alter the original appraisal processes underlying the feeling.     

Regression spline bivariate probit models: A practical approach to testing for exogeneity

Bivariate probit models can deal with a problem usually known as endogeneity. This issue is likely to arise in observational studies when confounders are unobserved. We are concerned with testing the hypothesis of exogeneity (or absence of endogeneity) when using regression spline recursive and sample selection bivariate probit models. Likelihood ratio and gradient tests are discussed in this context and their empirical properties investigated and compared with those of the Lagrange multiplier and Wald tests through a Monte Carlo study. The tests are illustrated using two datasets in which the hypothesis of exogeneity needs to be tested.     

A Bayesian Approach to Modelling Reticulation Events with Application to the Ribosomal Protein Gene rps11 of Flowering Plants

Traditional phylogenetic inference assumes that the history of a set of taxa can be explained by a tree. This assumption is often violated as some biological entities can exchange genetic material giving rise to non‐treelike events often called reticulations. Failure to consider these events might result in incorrectly inferred phylogenies. Phylogenetic networks provide a flexible tool which allows researchers to model the evolutionary history of a set of organisms in the presence of reticulation events. In recent years, a number of methods addressing phylogenetic network parameter estimation have been introduced. Some of them are based on the idea that a phylogenetic network can be defined as a directed acyclic graph. Based on this definition, we propose a Bayesian approach to the estimation of phylogenetic network parameters which allows for different phylogenies to be inferred at different parts of a multiple DNA alignment. The algorithm is tested on simulated data and applied to the ribosomal protein gene rps11 data from five flowering plants, where reticulation events are suspected to be present. The proposed approach can be applied to a wide variety of problems which aim at exploring the possibility of reticulation events in the history of a set of taxa.     

A hierarchical modelling approach for measuring reliability of and agreement between two types of magnetic field dosimeter

Summary.  The paper describes how to use hierarchical models to assess the reliability of and agreement between two or more types of measurement device. The idea is illustrated by fitting a linear model with nested random effects to a set of data that was obtained from the calibration of two samples of extremely low frequency magnetic field meters. The paper focuses on the formulation of a suitable model that accounts for the various aspects of the calibration protocol and the subsequent interpretation of the parameter estimates. The approach is very flexible and can easily be tuned to the various needs arising in the measurement agreement framework. It can be seen as an extension of the common practice of using a one-way random-effects model to retrieve a measure of agreement.