Somebody versus nobody: An exploration of the role of celebrity status in an election

This study examines the role celebrity status may play in potential voters’ evaluation of a political candidate presented in a newspaper article. Participants indicated greater intention to vote for a candidate who was a recognizable Hollywood actor than an unknown candidate in a political race, regardless of how substantive the political information provided about the candidate was. This suggests that familiarity with a celebrity can act as a heuristic in peripheral processing. Younger people were more likely to vote for a celebrity candidate than older voters, but how liberal or conservative participants are was not a significant factor in the decision to vote for the celebrity. Nor did participants’ need for cognition or level of political involvement predict intention to vote for the celebrity, suggesting that celebrity status is meaningful to motivated and thoughtful voters as well as those who are less motivated and informed. The possibility is raised that this could be an indication of celebrity status being used as a component of deliberate political decision-making, and future research in this direction is suggested.     

Mind-Reading and Metacognition: Narcissism, not Actual Competence, Predicts Self-Estimated Ability

In this paper, we examine the relationship between people's actual interpersonal sensitivity (such as their ability to identify deception and to infer intentions and emotions) and their perceptions of their own sensitivity. Like prior scholars, we find the connection is weak or non-existent and that most people overestimate their social judgment and mind-reading skills. Unlike previous work, however, we show new evidence about who misunderstands their sensitivity and why. We find that those who perform the worst in social judgment and mind-reading radically overestimate their relative competence. We also find origins of these self-estimates in general narcissistic tendencies toward self-aggrandizement. We discuss evidence from two studies, one involving the Interpersonal Perception Task (the IPT-15) and another focusing on inferences about partners after a face-to-face negotiation exercise. In both cases, actual performance did not predict self-estimated performance but narcissism did.     

Subjective Health-Related Quality of Life in Homeless and Vulnerably Housed Individuals and Its Relationship with Self-Reported Physical and Mental Health Status

Although the association between homelessness and objective indicators of poor health is well-established, little research has focused on the subjective health-related quality of life of homeless and vulnerably housed (HVH) individuals. This study examined the subjective health-related quality of life of HVH individuals, using the Multiple Discrepancies Theory (MDT) Scale for Health of the Quality of Life for Homeless and Hard-to-House Individuals (QoLHHI) Inventory, and its association with self-reported functional health status, as measured by the SF-12, and self-reported physical and mental health conditions in a sample of 100 HVH individuals recruited in Vancouver, Toronto and Ottawa. Our findings indicate that physical and mental health conditions are highly prevalent among HVH individuals and that the SF-12 Physical and Mental Component Summary scores are substantially lower compared to US population norms. The MDT Health items were not statistically significantly associated with physical or mental health conditions and only showed correlations of small to moderate magnitude with the SF-12 Component Summary Scales. These findings suggest that the QoLHHI MDT Scale for Health can provide information about HVH individuals’ subjective health experiences that is different from, and can serve as a valuable complement to, health status information for use in research and evaluation studies, as well as for policy purposes to make informed decisions based on subjective health-related quality of life data from HVH individuals.     

Feature selection and machine learning with mass spectrometry data for distinguishing cancer and non-cancer samples

This is a comparative study of various clustering and classification algorithms as applied to differentiate cancer and non-cancer protein samples using mass spectrometry data. Our study demonstrates the usefulness of a feature selection step prior to applying a machine learning tool. A natural and common choice of a feature selection tool is the collection of marginal p-values obtained from t-tests for testing the intensity differences at each m/z ratio in the cancer versus non-cancer samples. We study the effect of selecting a cutoff in terms of the overall Type 1 error rate control on the performance of the clustering and classification algorithms using the significant features. For the classification problem, we also considered m/z selection using the importance measures computed by the Random Forest algorithm of Breiman. Using a data set of proteomic analysis of serum from ovarian cancer patients and serum from cancer-free individuals in the Food and Drug Administration and National Cancer Institute Clinical Proteomics Database, we undertake a comparative study of the net effect of the machine learning algorithm–feature selection tool–cutoff criteria combination on the performance as measured by an appropriate error rate measure.     

Flexible models for non-equidispersed count data: comparative performance of parametric models to deal with underdispersion

AStA Advances in Statistical Analysis - Count data as response variables are commonly modeled using Poisson regression models, which require equidispersion, i.e., equal mean and variance. However,...     

Newborns' Perceptual Categorization for Closed and Open Geometric Forms

This study explored newborns' ability to perceive perceptual similarities between different exemplars of 2 broad classes of simple shapes: closed and open geometric forms. Three experiments were carried out using a visual paired‐comparison task. Evidence showed that, after familiarization either to closed‐shaped or to open‐shaped forms, newborns manifested a novelty preference for a novel‐category rather than for a familiar‐category exemplar (Experiment 1). This result could not be explained either as a consequence of the newborns' inability to discriminate between instances of the same category of simple geometric forms (Experiment 2), or as a consequence of a spontaneous preference for the novel‐category exemplars (Experiment 3). Overall, findings revealed that newborns are able to form broad categories of distinguishable geometric shapes by relying on the shapes' perceptual similarity.     

Parametric estimation for ARFIMA models via spectral methods

Given a fractional integrated, autoregressive, moving average,ARFIMA (p, d, q) process, the simultaneous estimation of the short and long memory parameters can be achieved by maximum likelihood estimators. In this paper, following a two-step algorithm, the coefficients are estimated combining the maximum likelihood estimators with the general orthogonal decomposition of stochastic processes. In particular, the principal component analysis of stochastic processes is exploited to estimate the short memory parameters, which are plugged into the maximum likelihood function to obtain the fractional differencingd.     

Yearning, learning, and conceding: reasons men and women change their childbearing intentions

People's childbearing intentions change over the course of their reproductive lives. These changes have been conceptualized as occurring in response to the realization that an individual is unlikely to achieve his or her intended fertility, because of constraints such as the "biological clock" or lack of a partner. In this article, we find that changes to child-bearing plans are influenced by a much wider range of factors than this. People change their plans in response to the wishes of their partners, in response to social norms, as the result of repartnering, and as the result of learning about the costs and benefits of parenthood; there are also differences between the factors that influence men's and women's decision-making. In a departure from existing studies in this area, we use a flexible analytical framework that enables us to analyze increases in planned fertility separately from decreases. This allows us to uncover several complexities of the decision-making process that would otherwise be hidden, and leads us to conclude that the determinants of increases in planned fertility are not simply equal and opposite to the determinants of decreases.