HIV/AIDS stigma manifestations during clinical interactions with MSM in Puerto Rico

HIV/AIDS stigma can have detrimental effects on physician/patient interactions when manifested by health professionals. Unfortunately, HIV/AIDS stigma is usually manifested in an intersectional manner with other preexisting stigmas, including stigma toward men who have sex with men (MSM). Therefore, our study aimed to examine the behavioral manifestations of HIV/AIDS stigma among physicians in training during simulated clinical interactions with MSM, and explore the interrelation between HIV/AIDS stigma attitudes and behaviors. We implemented an experimental design using Standardized Patient simulations with a sample of 100 physicians in training in Puerto Rico. Results show a significant difference in the two groups’ means (p?<?.001), with a higher number of stigma behaviors in the HIV MSM patient condition (M?=?6.39) than the common cold control condition (M?=?5.20). Results evidence that stigma manifestations toward MSM with HIV may continue to be an obstacle for public health in Puerto Rico, and that medical training to prevent stigma is still needed.     

Estimation and regularization techniques for regression models with multidimensional prediction functions

Boosting is one of the most important methods for fitting regression models and building prediction rules. A notable feature of boosting is that the technique can be modified such that it includes a built-in mechanism for shrinking coefficient estimates and variable selection. This regularization mechanism makes boosting a suitable method for analyzing data characterized by small sample sizes and large numbers of predictors. We extend the existing methodology by developing a boosting method for prediction functions with multiple components. Such multidimensional functions occur in many types of statistical models, for example in count data models and in models involving outcome variables with a mixture distribution. As will be demonstrated, the new algorithm is suitable for both the estimation of the prediction function and regularization of the estimates. In addition, nuisance parameters can be estimated simultaneously with the prediction function.     

Partial Least Squares: A First-order Analysis

We compare the partial least squares (PLS) and the principal component analysis (PCA), in a general case in which the existence of a true linear regression is not assumed. We prove under mild conditions that PLS and PCA are equivalent, to within a first-order approximation, hence providing a theoretical explanation for empirical findings reported by other researchers. Next, we assume the existence of a true linear regression equation and obtain asymptotic formulas for the bias and variance of the PLS parameter estimator     

ELECTORAL RULES AND CORRUPTION

Is corruption systematically related to electoral rules? Recent theoretical work suggests a positive answer. But little is known about the data. We try to address this lacuna by relating corruption to different features of the electoral system in a sample of about eighty democracies in the 1990s. We exploit the cross‐country variation in the data, as well as the time variation arising from recent episodes of electoral reform. The evidence is consistent with the theoretical priors. Larger voting districts—and thus lower barriers to entry—are associated with less corruption, whereas larger shares of candidates elected from party lists—and thus less individual accountability—are associated with more corruption. Individual accountability appears to be most strongly tied to personal ballots in plurality‐rule elections, even though open party lists also seem to have some effect. Because different aspects roughly offset each other, a switch from strictly proportional to strictly majoritarian elections only has a small negative effect on corruption. (JEL: E62, H3)     

Secondary agency conflicts: A synthesis and proposed measurement model

Secondary agency conflicts typically arise when ownership and control are combined in the hands of dominant shareholders who could then seek to misappropriate returns at the expense of minority shareholders. This type of agency conflict has attracted attention from researchers for the past nearly three decades. However, efforts at measuring secondary agency conflicts have been fragmented and scattered. The absence of a coherent and valid approach to assess the scope and intensity of secondary agency conflicts has impeded progress in both empirical and conceptual development of the topic area. Based on a review of the extant body of literature, this paper develops a composite Shareholder Inequity index that measures the potential for secondary agency conflicts employing three different governance dimensions that are grounded in the agency literature: blockholder power, differential control, and the absence of board neutrality. The index is tested and validated empirically using a sample of 748 publicly listed U.S. firms. The resulting Shareholder Inequity index demonstrates high levels of validity and reliability. Future corporate governance studies can utilize this validated measure to investigate potential secondary agency conflicts more consistently and rigorously in order to strengthen organizational theory development and research.     

A note On outlier sensitivity of Sliced Inverse Regression

Sliced Inverse Regression (SIR) is a promising technique for the purpose of dimension reduction. Several properties of this method have been examined already, but little attention has been paid to robustness aspects. In this article, we focus on the sensitivity of SIR to outliers and show in what sense and how severely SIR can be influenced by outliers in the data.     

Small Steps that Matter: Incremental Learning,Slack Resources and Organizational Performance

This paper examines the antecedents, consequences and moderators of incremental learning capabilities, understood as an organization's ability to gradually adapt and expand its knowledge base. Conceptualized as a dynamic capability, incremental learning is expected to be a vital driver of organizational adaptation. As dynamic capabilities consist of bundles of relatively stable routines, it is proposed that an organization's level of incremental learning capabilities will be highly persistent over time. It is also argued that building and exercising incremental learning capabilities is resource intensive and will as such tend to rely on the availability of sufficient slack resources. Last, it is suggested that incremental learning will be positively related to organizational performance, especially when the underlying business model is labour rather than capital intensive. To test these theoretical ideas, the authors draw on extensive panel data from all public non‐specialist hospitals in England and find broad support for their hypotheses.