American and Chinese College Students’ Anticipations of Their Postgraduate Education, Career, and Future Family Roles

American and Chinese college students’ anticipations showed no gender differences in their desires for postgraduate education, marriage, and parental status. Stereotypical gender differences emerged in both countries when caregiving roles were considered: Both men and women rated it more likely for women than for men to quit their jobs to be caregivers. Overall, male college students, the Chinese men in particular, felt less comfortable than did women in situations where their spouses were superior in earnings, achievements, and social status. More Chinese than American students planned to enter marriage and parenthood at a later age, and the Chinese students rated the importance of family lower. These findings are discussed in light of the general sociocultural model and the role distribution theory.This study was supported partially by a summer mini-grant issued by the University of St. Francis in 2000.     

Preference for distribution by equal outcome in 5- and 6-year-old children

This study investigated preferences for types of fairness applied in resource distribution. We consider two types of equal distribution: according to the equal-allocation principle (new resources are distributed evenly without considering currently possessed resources) or the equal-outcome principle (equal outcome amounts result after distribution because current resources are considered). Children aged 5–6 and adults participated. The participant initially had two sets of two marbles (participant condition) or each of two puppets initially had two marbles (puppet condition). Then one puppet distributed new marbles between itself and the participant by equal-outcome. Next, the other puppet distributed new marbles by equal-allocation. The results showed that the majority of children and adults selected the distribution by equal-outcome for both conditions. This suggests that people prefer distribution by equal-outcome to distribution by equal-allocation. However, some children aged 5–6 thought that distribution by equal-allocation was better only when they already had resources.     

Robust Bayesian growth curve modelling using conditional medians

Growth curve models have been widely used to analyse longitudinal data in social and behavioural sciences. Although growth curve models with normality assumptions are relatively easy to estimate, practical data are rarely normal. Failing to account for non-normal data may lead to unreliable model estimation and misleading statistical inference. In this work, we propose a robust approach for growth curve modelling using conditional medians that are less sensitive to outlying observations. Bayesian methods are applied for model estimation and inference. Based on the existing work on Bayesian quantile regression using asymmetric Laplace distributions, we use asymmetric Laplace distributions to convert the problem of estimating a median growth curve model into a problem of obtaining the maximum likelihood estimator for a transformed model. Monte Carlo simulation studies have been conducted to evaluate the numerical performance of the proposed approach with data containing outliers or leverage observations. The results show that the proposed approach yields more accurate and efficient parameter estimates than traditional growth curve modelling. We illustrate the application of our robust approach using conditional medians based on a real data set from the Virginia Cognitive Aging Project.     

Gender differences existing in the general population in relation to body dissatisfaction associated with the ideal of beauty: a systematic review / Diferencias de género existentes en la población general en relación a la insatisfacción corporal asociada al ideal de belleza: una revisión sistemática

Abstract

Body dissatisfaction has been studied extensively due to its relationship with issues such as eating disorders, mainly in the female and adolescent population. However, it seems that there are differences in the type of body dissatisfaction that females and males manifest with respect to their body image. On this basis, the objective of this work was to review systematically the studies published from 2010 to July 2018 into gender differences in body dissatisfaction associated with the ideal of beauty in the general population. A total of 18 studies were selected from the MeSH/PubMed, Dialnet and DOAJ databases. The results obtained from the studies analysed showed that the female population continues to show greater body dissatisfaction associated with the ideal of beauty compared to the male population. However, the manifestation of body dissatisfaction is expressed differently for men and women.     

A new variable interval schedule with constant hazard rate and finite time range

We propose a new variable interval (VI) schedule that achieves constant probability of reinforcement in time while using a bounded range of intervals. By sampling each trial duration from a uniform distribution ranging from 0 to 2 T seconds, and then applying a reinforcement rule that depends linearly on trial duration, the schedule alternates reinforced and unreinforced trials, each less than 2 T seconds, while preserving a constant hazard function.     

Approximations to the distribution of a test statistic in covariance structure analysis: A comprehensive study

In structural equation modelling (SEM), a robust adjustment to the test statistic or to its reference distribution is needed when its null distribution deviates from a χ² distribution, which usually arises when data do not follow a multivariate normal distribution. Unfortunately, existing studies on this issue typically focus on only a few methods and neglect the majority of alternative methods in statistics. Existing simulation studies typically consider only non-normal distributions of data that either satisfy asymptotic robustness or lead to an asymptotic scaled χ² distribution. In this work we conduct a comprehensive study that involves both typical methods in SEM and less well-known methods from the statistics literature. We also propose the use of several novel non-normal data distributions that are qualitatively different from the non-normal distributions widely used in existing studies. We found that several under-studied methods give the best performance under specific conditions, but the Satorra–Bentler method remains the most viable method for most situations.     

A scaled difference chi-square test statistic for moment structure analysis

A family of scaling corrections aimed to improve the chi-square approximation of goodness-of-fit test statistics in small samples, large models, and nonnormal data was proposed in Satorra and Bentler (1994). For structural equations models, Satorra-Bentler's (SB) scaling corrections are available in standard computer software. Often, however, the interest is not on the overall fit of a model, but on a test of the restrictions that a null model sayM ₀ implies on a less restricted oneM ₁. IfT ₀ andT ₁ denote the goodness-of-fit test statistics associated toM ₀ andM ₁, respectively, then typically the differenceT _d =T ₀−T ₁ is used as a chi-square test statistic with degrees of freedom equal to the difference on the number of independent parameters estimated under the modelsM ₀ andM ₁. As in the case of the goodness-of-fit test, it is of interest to scale the statisticT _d in order to improve its chi-square approximation in realistic, that is, nonasymptotic and nonormal, applications. In a recent paper, Satorra (2000) shows that the difference between two SB scaled test statistics for overall model fit does not yield the correct SB scaled difference test statistic. Satorra developed an expression that permits scaling the difference test statistic, but his formula has some practical limitations, since it requires heavy computations that are not available in standard computer software. The purpose of the present paper is to provide an easy way to compute the scaled difference chi-square statistic from the scaled goodness-of-fit test statistics of modelsM ₀ andM ₁. A Monte Carlo study is provided to illustrate the performance of the competing statistics. This research was supported by the Spanish grants PB96-0300 and BEC2000-0983, and USPHS grants DA00017 and DA01070.     

The Effect of the Balance of Orthographic Neighborhood Distribution in Visual Word Recognition

The present study investigated whether the balance of neighborhood distribution (i.e., the way orthographic neighbors are spread across letter positions) influences visual word recognition. Three word conditions were compared. Word neighbors were either concentrated on one letter position (e.g.,nasse/basse-lasse-tasse-masse) or were unequally spread across two letter positions (e.g.,pelle/celle-selle-telle-perle), or were equally spread across two letter positions (e.g.,litre/titre-vitre-libre-livre). Predictions based on the interactive activation model [McClelland & Rumelhart (1981). Psychological Review, 88, 375–401] were generated by running simulations and were confirmed in the lexical decision task. Data showed that words were more rapidly identified when they had spread neighbors rather than concentrated neighbors. Furthermore, within the set of spread neighbors, words were more rapidly recognized when they had equally rather than unequally spread neighbors. The findings are explained in terms of activation and inhibition processes in the interactive activation framework.     

Aging and intraindividual variability in performance: analyses of response time distributions

It has been suggested that older adults are more variable in their performance because they are more prone to lapses of either attention or intention. In the present experiment, 9 young and 9 older adults each performed nearly 2000 trials of a same-different judgment task. As expected, older adults were slower and more variable than young adults. When the age-related difference in speed was taken into account, however, the older adults were, if anything, less variable than the young adults. When younger and older adults' RT distributions were analyzed using quantile-quantile plots and by fitting ex-Gaussian and Weibull functions, there was no consistent evidence that older adults' distributions were more skewed than young adults', as would be predicted by age-related increases in lapses of attention or intention. Importantly, there was a positive, linear relation between RT and intraindividual variability, and the same relation was observed both within subjects (practice increased speed and reduced variability) as well as between subjects (regardless of age, slower individuals were more variable). Thus, the present results suggest that there may be a general law governing the relation between average RT and variability, and that the greater performance variability of older adults primarily reflects their greater average RTs.