A comparison of classification models to identify the Fragile X Syndrome

The main models of machine learning are briefly reviewed and considered for building a classifier to identify the Fragile X Syndrome (FXS). We have analyzed 172 patients potentially affected by FXS in Andalusia (Spain) and, by means of a DNA test, each member of the data set is known to belong to one of two classes: affected, not affected. The whole predictor set, formed by 40 variables, and a reduced set with only nine predictors significantly associated with the response are considered. Four alternative base classification models have been investigated: logistic regression, classification trees, multilayer perceptron and support vector machines. For both predictor sets, the best accuracy, considering both the mean and the standard deviation of the test error rate, is achieved by the support vector machines, confirming the increasing importance of this learning algorithm. Three ensemble methods - bagging, random forests and boosting - were also considered, amongst which the bagged versions of support vector machines stand out, especially when they are constructed with the reduced set of predictor variables. The analysis of the sensitivity, the specificity and the area under the ROC curve agrees with the main conclusions extracted from the accuracy results. All of these models can be fitted by free R programs.     

`Sex-Equal' Stable Matchings

The paper defines a measure on the set of stable matchings in the marriage problem. This measure is based on the minimization of the envy difference between the sets of men and women, while preserving stability and selects stable matchings with the least conflict of interest between both groups of agents. The solution concept proposed is called Sex-equal Matching (SEM) and the paper also provides an algorithm to compute the set of SEM.     

Longitudinal Mediators of Relations Between Family Violence and Adolescent Dating Aggression Perpetration

Few longitudinal studies have examined the pathways through which family violence leads to dating aggression. In the current study the authors used 3 waves of data obtained from 8th‐ and 9th‐grade adolescents (N = 1,965) to examine the hypotheses that the prospective relationship between witnessing family violence and directly experiencing violence and physical dating aggression perpetration is mediated by 3 constructs: (a) normative beliefs about dating aggression (norms), (b) anger dysregulation, and (c) depression. Results from cross‐lagged regression models suggest that the relationship between having been hit by an adult and dating aggression is mediated by changes in norms and anger dysregulation, but not depression. No evidence of indirect effects from witnessing family violence to dating aggression was found through any of the proposed mediators. Taken together, the findings suggest that anger dysregulation and normative beliefs are potential targets for dating abuse prevention efforts aimed at youth who have directly experienced violence.     

Social mobility and demand for redistribution in Europe: a comparative analysis

The literature on preferences for redistribution has paid little attention to the effect of social mobility on the demand for redistribution and no systematic test of the hypotheses connecting social mobility and preferences for redistribution has yet been done to date. We use the diagonal reference model to estimate the effect of origin and destination classes on preferences for redistribution in a large sample of European countries using data from the European Social Survey. Our findings are consistent with the logic of acculturation in the sense that newcomers tend to adapt their views to those of the destination class at early stages and that upward and downward mobility do not have distinctive effects on the formation of political preferences. However, even though social origins seem to have a limited impact on preferences for redistribution, the evidence does not support the hypothesis that mobile and non‐mobile individuals are alike. We also find that the effect of social origin on preferences varies largely across countries. The empirical evidence leads to the conclusion that the effect of social origin on preferences for redistribution increases in contexts of strong familism.     

Physical activity is inversely related to drug consumption in elderly patients with cardiovascular events

Elderly patients with cardiovascular events are characterized by high drug consumptions. Whether high drug consumptions are related to physical activity is not known. In order to examine whether physical activity is related to drug consumption in the elderly, patients older than 65 years (n?=?250) with a recent cardiovascular event were studied. Physical activity was analyzed according to the Physical Activity Scale for the Elderly (PASE) score and related to drug consumption. PASE score was 72.4?±?45.0 and drug consumption was 8.3?±?2.2. Elderly patients with greater comorbidity took more drugs (8.7?±?2.1) and are less active (PASE?=?64.4?±?50.6) than patients with Cumulative Illness Rating Scale severity score higher than 1.8 than those with a score lower than 1.8 (76.3?±?41.4, p?<?0.05, and 8.0?±?2.0, p?=?0.006, respectively). Multivariate analysis correlation confirmed that PASE score is negatively associated with drug consumption (β?=??0.149, p?=?0.031), independently of several variables including comorbidity. Thus, physical activity is inversely related to drug consumption in elderly patients with cardiovascular events. This inverse relationship may be attributable to the high degree of comorbidity observed in elderly patients in whom poor level of physical activity and high drug consumption are predominant.     

Trend smoothness achieved by penalized least squares with the smoothing parameter chosen by optimality criteria

This work presents a study about the smoothness attained by the methods more frequently used to choose the smoothing parameter in the context of splines: Cross Validation, Generalized Cross Validation, and corrected Akaike and Bayesian Information Criteria, implemented with Penalized Least Squares. It is concluded that the amount of smoothness strongly depends on the length of the series and on the type of underlying trend, while the presence of seasonality even though statistically significant is less relevant. The intrinsic variability of the series is not statistically significant and its effect is taken into account only through the smoothing parameter.     

Voting in professional associations: The case of the American sociological association revisited

Who votes in ASA elections? This article examines data on voter turnout from two recent presidential contests of the American Sociological Association in an analysis of the determinants of election participation. Extending the 1981 Ridgeway and Moore study of voting dynamics in the ASA, we hypothesize that intraorganizational networks and particular demongraphic characteristics link ASA members to the discipline in a manner analogous to the way such factors operate in the national electorate. On the basis of data compiled from 1985 and 1986 ASA election returns, we find that network factors are the most salient determinants of voting behavior. We conclude that those organizational ties that effectively link members, however directly or indirectly, to the larger Association are the most predictive of propensity to vote.