109 research outputs found

    A population-modulated bibliometric measure with an application in the field of statistics

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    We use confirmatory factor analysis to derive a unifying measure of comparison of scientists based on bibliometric measurements, by utilizing the h-index, some similar h-type indices as well as other common measures of scientific performance. We use a real data example from nine well-known departments of statistics to demonstrate our approach and argue that our combined measure results in a better overall evaluation of a researchers' scientific work

    Maintaining (locus of) control? : Assessing the impact of locus of control on education decisions and wages

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    This paper establishes that individuals with an internal locus of control, i.e., who believe that reinforcement in life comes from their own actions instead of being determined by luck or destiny, earn higher wages. However, this positive effect only translates into labor income via the channel of education. Factor structure models are implemented on an augmented data set coming from two different samples. By so doing, we are able to correct for potential biases that arise due to reverse causality and spurious correlation, and to investigate the impact of premarket locus of control on later outcomes

    A study of genetic and environmental influences on maternal and paternal CBCL syndrome scores in a large sample of 3-year-old Dutch twins.

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    Background. There is increasing evidence that behavioral problems are common in very young children, yet little is known about the etiology of individual differences in these problems. It is unclear to what degree environmental and genetic factors influence the development of early child psychopathology. In this paper, we focus on the following issues. Firstly, to what degree do genetic and environmental factors influence variation in behavioral problems? Secondly, to what degree are these underlying etiological factors moderated by sex and informant? We investigate these issues by analyzing Child Behavior Checklist (CBCL) data on 9689 3-year-old twin pairs. Methods. Rater Bias and Psychometric Models were fitted to CBCL/2-3 data obtained from mothers and fathers to determine the genetic and environmental contributions to the five CBCL syndromes:aggressive, oppositional, overactive, withdrawn, and anxious/depressed behavior. Results. Parental ratings are influenced by aspects of the child's behavior that are experienced in the same way by both parents and by aspects of the child's behavior that are experienced uniquely by each parent. There is evidence for high genetic contributions to all CBCL syndromes. Shared and non-shared environmental influences play significant roles as well. One exception is overactive behavior, which is influenced by genetic and non-shared environmental influences only. Conclusions. Variation in behavior problems in the very young shows high heritability. Individual raters offer unique perspectives that can have an impact on estimates of problem behavior and genetic architecture. Therefore, multi-informant approaches in the assessment of the very young will be useful to clinicians and researchers alike

    Development and Validation of the Retrospective Childhood Fantasy Play Scale

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    Kirkham, J, A., Lloyd, J., & Stockton, H, Development and validation of the retrospective childhood fantasy play scale, Imagination, Cognition and Personality (2018) Vol. 38 Iss. 3 pp. 315-344. Copyright © 2018 SAGE. Reprinted by permission of SAGE Publications.This article describes the development and initial psychometric properties of the Retrospective Childhood Fantasy Play Scale (RCFPS), a brief 11-item retrospective self-report measure of reference for, and engagement with, fantasy play during childhood. Five studies were conducted to (a) develop the initial items for the scale (n =77), (b) determine the underlying factor structure (n = 200), (c) test the fit of the model (n= 530), and (d) and (e) ascertain construct validity (n = 200) and convergent validity (n = 263). Overall, the results suggest that the RCFPS is a unidimensional measure with acceptable fit and preliminary validity. The RCFPS may prove useful in educational and developmental research as an alternative to longitudinal studies to further investigate how childhood fantasy play relates to individual differences in adulthood (e.g., in the areas of creativity, theory of mind, and narrative skills)

    What Makes Retirees Happier: A Gradual or 'Cold Turkey' Retirement?

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    This study explores the factors that affect an individual’s happiness while transitioning into retirement. Recent studies highlight gradual retirement as an attractive option to older workers as they approach full retirement. However, it is not clear whether phasing or cold turkey makes for a happier retirement. Using longitudinal data from the Health and Retirement Study, this study explores what shapes the change in happiness between the last wave of full employment and the first wave of full retirement. Results suggest that what really matters is not the type of transition (gradual retirement or cold turkey), but whether people perceive the transition as chosen or forced

    The empirics of social capital and economic development: a critical perspective

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    This paper provides an introduction to the concept of social capital, and carries out a critical review of the empirical literature on social capital and economic development. The survey points out six main weaknesses affecting the empirics of social capital. Identified weaknesses are then used to analyze, in a critical perspective, some prominent empirical studies and new interesting researches published in last two years. The need emerges to acknowledge, also within the empirical research, the multidimensional, context-dependent and dynamic nature of social capital. The survey also underlines that, although it has gained a certain popularity in the empirical research, the use of “indirect” indicators may be misleading. Such measures do not represent social capital’s key components identified by the theoretical literature, and their use causes a considerable confusion about what social capital is, as distinct from its outcomes, and what the relationship between social capital and its outcomes may be. Research reliant upon an outcome of social capital as an indicator of it will necessarily find social capital to be related to that outcome. This paper suggests to focus the empirical research firstly on the “structural” aspects of the concept, therefore excluding by the measurement toolbox all indicators referring to social capital’s supposed outcomes

    A Simulation Study to Compare Competing Estimators in Structural Equation Models with Ordinal Variables

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    Structural equation models have been around for now a long time. They are intensively used to analyze data from di.erent fields such as psychology, social sciences, economics, management, etc. Their estimation can be performed using standard statistical packages such as LISREL. However, these implementations su.er from an important drawback: they are not suited for cases in which the variables are far from the normal distribution. This happens in particular with ordinal data that have a non symmetric distribution, a situation often encountered in practice. An alternative approach would be to use generalized linear latent variable models (GLLVM) as defined for example in Bartholomew and Knott 1999 and Moustaki and Knott (2000). These models consider the data as they are, i.e. binary or ordinal but the loglikelihood function is intractable and needs numerical approximations to compute it. Several approaches exist such as Gauss-Hermite quadratures or simulation based methods, as well as the Laplace approximation, i.e. the Laplace approximated maximum likelihood estimator (LAMLE) proposed by Huber, Ronchetti, and Victoria-Feser (2004) for these models. The advantage of the later is that it is very fast and hence can cope with relatively complicated models. In this paper, we perform a simulation study to compare the parameters' estimators provided by LISREL which is taken as a benchmark, and the LAMLE when the data are generated from a confirmatory factor analysis model with normal variables which are then transformed into ordinal ones. We will show that while the LISREL estimators can provide seriously biased estimators, the LAMLE not only is unbiased, but one can also recover an unbiased estimator of the correlation matrix of the original normal variables
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