Screens across the pond: Findings from longitudinal screen time research in the US and UK

Digital media are increasingly pervasive in the lives of young children. This increase in the availability of digital media might have long-run implications for child development; however, it is too soon to definitively conclude the direction of effects. In part due to this lack of certainty, leading health organizations have chosen to make different recommendations to parents of young children: Many international health organizations (e.g., the American Academy of Pediatrics, World Health Organization) recommend very young children be limited to under one hour of screen time daily, whereas others (e.g., Royal College of Paediatrics and Child Health) have intentionally opted not to make recommendations about specific limits. These guidelines might contribute to parents in different countries making meaningfully different choices about children’s use of digital media. Using a sample of N = 303 families recruited in Cambridgeshire, England and New York City prior to the birth of couples’ first child, we explore predictors of digital media use across the first two years of life. Data were collected when children were 4, 14, and 24 months of age. Results of latent growth curve analyses show that generally, children spend more time engaging with digital media as they grow older; however, growth mixture models reveal most children fit into one of two classes: One group of children (High Media Users; 52.2 %) engages with a substantial amount of digital media, whereas the other (Low Media Users; 48.8 %) engages with relatively little. Children in the US were approximately 30 % more likely to be in the Low Media Users group and there were no differences in group membership on the basis of parents’ psychosocial wellbeing. While these differences could be due to a number of factors, these findings may reflect the power of pediatric recommendations.     

The dynamics of fidelity over the time course of long-term memory

Bayesian models of cognition assume that prior knowledge about the world influences judgments. Recent approaches have suggested that the loss of fidelity from working to long-term (LT) memory is simply due to an increased rate of guessing (e.g. Brady, Konkle, Gill, Oliva, & Alvarez, 2013). That is, recall is the result of either remembering (with some noise) or guessing. This stands in contrast to Bayesian models of cognition while assume that prior knowledge about the world influences judgments, and that recall is a combination of expectations learned from the environment and noisy memory representations. Here, we evaluate the time course of fidelity in LT episodic memory, and the relative contribution of prior category knowledge and guessing, using a continuous recall paradigm. At an aggregate level, performance reflects a high rate of guessing. However, when aggregate data is partitioned by lag (i.e., the number of presentations from study to test), or is un-aggregated, performance appears to be more complex than just remembering with some noise and guessing. We implemented three models: the standard remember-guess model, a three-component remember-guess model, and a Bayesian mixture model and evaluated these models against the data. The results emphasize the importance of taking into account the influence of prior category knowledge on memory.     

A Person‐Centered Perspective on Multidimensional Perfectionism in Canadian and Chinese University Students: A Multigroup Latent Profile Analysis

This study investigated the generalizability of the tripartite model of perfectionism across Canadian and Chinese university students. Using latent profile analysis and indicators of perfectionistic strivings, perfectionistic concerns, and neuroticism in both groups, the authors derived a 3‐profile solution: adaptive perfectionists, maladaptive perfectionists, and nonperfectionists. Furthermore, multigroup latent profile analysis supported the construct equivalence of the 3‐profile solution across groups. Results further suggested that a greater proportion of Chinese students could be classified as adaptive perfectionists. Este estudio investigó la generalizabilidad del modelo tripartito de perfeccionismo entre estudiantes universitarios canadienses y chinos. Usando un análisis de perfil latente e indicadores de esfuerzos perfeccionistas, preocupaciones perfeccionistas y neuroticismo en ambos grupos, los autores desarrollaron una solución de 3 perfiles: perfeccionistas adaptados, perfeccionistas inadaptados y no perfeccionistas. Además, el análisis de perfil latente multigrupo confirmó la equivalencia de constructo de la solución de 3 perfiles en estos grupos. Los resultados sugieren también que una mayor proporción de estudiantes chinos podría clasificarse como perfeccionistas adaptados.     

Bias-corrected estimation of the Rudas–Clogg–Lindsay mixture index of fit

Rudas, Clogg, and Lindsay (1994, J. R Stat Soc. Ser. B, 56, 623) introduced the so-called mixture index of fit, also known as pi-star (π*), for quantifying the goodness of fit of a model. It is the lowest proportion of ‘contamination’ which, if removed from the population or from the sample, makes the fit of the model perfect. The mixture index of fit has been widely used in psychometric studies. We show that the asymptotic confidence limits proposed by Rudas et al. (1994, J. R Stat Soc. Ser. B, 56, 623) as well as the jackknife confidence interval by Dayton ( 2003 , Br. J. Math. Stat. Psychol., 56, 1) perform poorly, and propose a new bias-corrected point estimate, a bootstrap test and confidence limits for pi-star. The proposed confidence limits have coverage probability much closer to the nominal level than the other methods do. We illustrate the usefulness of the proposed method in practice by presenting some practical applications to log-linear models for contingency tables.     

On measurement properties of continuation ratio models

Three classes of polytomous IRT models are distinguished. These classes are the adjacent category models, the cumulative probability models, and the continuation ratio models. So far, the latter class has received relatively little attention. The class of continuation ratio models includes logistic models, such as the sequential model (Tutz, 1990), and nonlogistic models, such as the acceleration model (Samejima, 1995) and the nonparametric sequential model (Hemker, 1996). Four measurement properties are discussed. These are monotone likelihood ratio of the total score, stochastic ordering of the latent trait by the total score, stochastic ordering of the total score by the latent trait, and invariant item ordering. These properties have been investigated previously for the adjacent category models and the cumulative probability models, and for the continuation ratio models this is done here. It is shown that stochastic ordering of the total score by the latent trait is implied by all continuation ratio models, while monotone likelihood ratio of the total score and stochastic ordering on the latent trait by the total score are not implied by any of the continuation ratio models. Only the sequential rating scale model implies the property of invariant item ordering. Also, we present a Venn-diagram showing the relationships between all known polytomous IRT models from all three classes.     

Nonparametric goodness-of-fit tests for the rasch model

A Monte Carlo algorithm realizing a family of nonparametric tests for the Rasch model is introduced which are conditional on the item and subject marginals. The algorithm is based on random changes of elements of data matrices without changing the marginals; most powerful tests against all alternative hypotheses are given for which a monotone characteristic may be computed from the data matrix; alternatives may also be composed. Computation times are long, but exactp-values are approximated with the quality of approximation only depending on calculation time, but not on the number of persons. The power and the flexibility of the procedure is demonstrated by means of an empirical example where, among others, indicators for increased item similarities, the existence of subscales, violations of sufficiency of the raw score as well as learning processes were found. Many of the features described are implemented in the program T-Rasch 1.0 by Ponocny and Ponocny-Seliger (1999).The author wishes to thank Alexander Kaba, Birgit Bukasa, and Ulrike Wenninger of Österreichisches Kuratorium für Verkehrssicherheit (Austrian Traffic Safety Board) for allowing a data set to be used for the empirical example, and Elisabeth Ponocny-Seliger and the reviewers for many helpful comments. The menu-driven program T-Rasch 1.0 by Ponocny and Ponocny-Seliger (1999) can be obtained from Assessment Systems Corporation (http: //www.assess.com) or from the authors. (Note that it also performs exact person fit tests.)     

Marginal maximum likelihood estimation of item response theory (IRT) equating coefficients for the common-examinee design

A method of estimating item response theory (IRT) equating coefficients by the common-examinee design with the assumption of the two-parameter logistic model is provided. The method uses the marginal maximum likelihood estimation, in which individual ability parameters in a common-examinee group are numerically integrated out. The abilities of the common examinees are assumed to follow a normal distribution but with an unknown mean and standard deviation on one of the two tests to be equated. The distribution parameters are jointly estimated with the equating coefficients. Further, the asymptotic standard errors of the estimates of the equating coefficients and the parameters for the ability distribution are given. Numerical examples are provided to show the accuracy of the method.     

应征公民计算机自适应化拼图测验的编制

在文献回顾和参考外军有关资料的基础上,根据项目反应理论和空间能力测验的有关理论编制试题库。首先采用纸笔测验的形式进行预实验,探讨采用IRT理论编制CAT拼图测验的可行性。然后,在预实验的基础上对试题进行修订并扩充试题数量,编制计算机辅助测验。选择三参数Logistic模型,采用铆题等值设计,分7份不同的试卷在全国征兵心理检测的过程中对55777名应征公民进行施测。根据测试结果,对题目进行分析,选择高质量的题目构成CAT试题库,采用a系数分层抽样的方法控制曝光率,并采用不同的测验终止策略编制CAT拼图测验。最后用WAIS智力测验积木分测验和三门功课的考试成绩为效标,通过72名被试对CAT拼图测验进行效度验证。结果显示该测验符合项目反应理论三参数Logistic模型的假设,各题目参数比较理想,所编制的测验具有较好的信度和效度,可用于应征公民心理选拔的实践     

基于GPCM的计算机自适应测验选题策略比较

选题策略是计算机自适应测验（Computerized Adaptive Testing , CAT）研究的一项重要内容,它的好坏直接关系到考试的信度、效度及考试的安全性。CAT的许多研究与应用,都建立在0-1二级评分模型基础上,对多级评分CAT的选题策略的研究很少报导。目前国内虽已开展了基于GRM的CAT研究,但基于GPCM的CAT的研究尚未见有关报道。本文通过计算机模拟程序,对基于拓广分部评分模型(Generalized Partial Credit Model, GPCM)下的CAT的四种选题策略在多种情况下进行了比较研究。研究结果表明：被试能力呈正态分布时,选题策略的使用效果与项目步骤参数分布有很大的关系。（1）项目步骤参数均服从正态分布时,采用能力与项目步骤参数匹配选题策略效果最佳;（2）项目步骤参数均服从均匀分布时,能力与项目步骤参数平均数匹配选题策略效果最佳     

Developmental Trajectories of Perceived Friendship Intimacy,Constructive Problem Solving,and Depression from Early to Late Adolescence

This study examined friendship types in developmental trajectories of perceived closeness and balanced relatedness. In addition, differences between friendship types in the development of constructive problem solving and depression were examined. Questionnaire data of five annual waves were used from two adolescent cohorts (cohort 1: M = 12.41 years; cohort 2: M = 16.37 years). Growth Mixture Modeling revealed two developmental trajectories in cognitive representations of perceived friendship intimacy: interdependent and disengaged friendships. Adolescents in interdependent friendships were characterized by high perceived closeness and balanced relatedness across adolescence. Furthermore, adolescents in disengaged friendships had lower levels of and smaller increases in constructive problem solving. Girls in disengaged friendships showed smaller increases in balanced relatedness and higher levels of depression than boys in disengaged friendships and adolescents in interdependent friendships.