Causal Ordering of Basic Psychological Needs and Well-Being

What is the relationship between well-being and satisfaction of basic psychological needs overtime? The basic psychological needs theory is a subtheory of the self-determination theory that elaborates the concept of psychological needs and its relations to psychological health and well-being. The goals of this research was to establish the causal ordering between basic psychological needs and three psychological well-being indicators (subjective well-being, self-esteem and satisfaction with life), in a longitudinal study. We used a cross-lagged two-wave design. A total of 272 university students completed the questionnaire at the beginning and at the end of the semester. Relatedness at time 1 (T₁) had a positive and significant effect on all well-being indicators at time 2 (T₂); competence (T₁) had a positive and significant effect on all indicators except for self-esteem (T₂); finally, autonomy (T₁) did not have a significant effect on any of the well-being indicators (T₂). In conclusion, we confirm the causal ordering of competence and relatedness on well-being, according to the basic psychological needs subtheory. Universities, in general, and teachers, in particular, should promote relations between students and support the need of competence.     

COWORDS: a probabilistic model for multiple word clouds

Word clouds constitute one of the most popular statistical tools for the visual analysis of text documents because they provide users with a quick and intuitive understanding of the content. Despite their popularity for visualizing single documents, word clouds are not appropriate to compare different text documents. Independently generating word clouds for each document leads to configurations where the same word is typically located in widely different positions. This makes it very difficult to compare two or more word clouds. This paper introduces COWORDS, a new stochastic algorithm to create multiple word clouds, including one for each document. The shared words in multiple documents are placed in the same position in all clouds. Similar documents produce similar and compact clouds, making it easier to simultaneously compare and interpret several word clouds. The algorithm is based on a probability distribution in which the most probable configurations are those with a desirable visual aspect, such as a low value for the total distance between the words in all clouds. The algorithm output is a set of word clouds that are randomly selected from this probability distribution. The selection procedure uses a Markov chain Monte Carlo simulation method. We present several examples that illustrate the performance and visual results that can be obtained by our algorithm.     

Estimating the population proportion in modified ranked set sampling methods

In this paper, proportion estimators and associated variance estimators are proposed for a binary variable with a concomitant variable based on modified ranked set sampling methods, which are extreme ranked set sampling (ERSS), median ranked set sampling (MRSS), percentile ranked set sampling (Per-RSS) and L ranked set sampling (LRSS) methods. The Monte Carlo simulation study is performed to compare the performance of the estimators based on bias, mean squared error, and relative efficiency for different levels of correlation coefficient, set and cycle sizes under normal and log-normal distributions. Moreover, the study is supported with real data application.     

Bayesian unit-root tests for Stochastic Volatility models

In this article, we consider Bayesian inference procedures to test for a unit root in Stochastic Volatility (SV) models. Unit-root tests for the persistence parameter of the SV models, based on the Bayes Factor (BF), have been recently introduced in the literature. In contrast, we propose a flexible class of priors that is non-informative over the entire support of the persistence parameter (including the non-stationarity region). In addition, we show that our model fitting procedure is computationally efficient (using the software WinBUGS). Finally, we show that our proposed test procedures have good frequentist properties in terms of achieving high statistical power, while maintaining low total error rates. We illustrate the above features of our method by extensive simulation studies, followed by an application to a real data set on exchange rates.     

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.     

Language in the process of labour market rationalisation: A sociohistorical approach across twentieth-century Spain

This article analyses the role of linguistic skills in the process of defining professional classifications in Spain during 1919–1980. The aim is to determine the social evaluation of the skills involved. To retrace the classifications, a total of 114 official documents were examined, establishing a chronological division into three major stages: 1920–1940, 1940–1960 and 1960–1980. The first period (1920–1940) shows efforts toward the initial objectification of working conditions and salary scales, revealing social prejudices and tacit conventions shaping the employment hierarchy, while the second one (1940–1960) indicates the extent to which office work stood out over manual work. Finally, the third stage (1960–1980) shows processes of language rationalisation, which entailed attempts to standardise positions based on required skill sets.     

Caseworkers as a source of hope leading to perceptions of academic success for transitional age foster youth

Research among adolescent samples has consistently demonstrated that a hopeful mindset is associated with resilience and global well-being. Further, research suggests that hope is influenced from an early age from connections with supportive caregivers. However, because older youth in the child welfare system may lack supportive caregivers, alternative sources of hope may be needed. To test a theory that supportive child welfare caseworkers can serve as external sources of hope, we conducted a cross-sectional study of youth in the child welfare system from a single state (N = 149). Using surveys with established scales to measure the variables of interest, the study tested a structural equation model of (1) youth's external hope in their caseworker as a driver of (2) internal hope in themselves leading to (3) more positive perceptions of academic success. Perceptions of academic success were chosen as the final consequence of the model because academic success has been linked to many other variables of well-being across the lifespan. The results indicate that the proposed structural model fits the data well (χ² = 327.9, df = 150; P < 0.001; root-mean-square error of approximation [RMSEA] = 0.09 [90% confidence interval – CI: 0.076, 0.103]; comparative fit index [CFI]: 0.920; standardized root-mean-square residual [SRMR]: 0.05). The results indicate that youths' hope in themselves had origins in external hope in the caseworker. Moreover, the final consequence was an increase in perceptions of academic success. Such results have implications by revealing how case management services can positively influence foster youths' hope and thereby influence their academic success.     

Social Competence in Preschool Children: Replication of Results and Clarification of a Hierarchical Measurement Model

This study tested assumptions and conclusions reached in an earlier confirmatory factor analysis (CFA) study of the social competence (SC) construct for preschool children. Two samples (total N = 408; a new Portuguese sample and one from US samples that had participated in the original study) contributed data. Seven SC indicators were tested for mean differences across age, sex, and sample. Significant sex differences were found for peer acceptance (favoring girls) and for initiating affectively neutral interactions (boys had higher rates), and the sex by sample interaction also was significant for initiating interactions (i.e., effect significant only in the Portuguese sample). In CFAs, the hypothesized structure of SC fits the data and was invariant across sample and age within sample in both measurement and structural tests. The model was invariant at the measurement level for sex within sample tests, but not at the structural level. The results replicate and extend understandings of SC reported in the original study.