A Multilevel Contextual Model of Neighborhood Collective Efficacy

Different data sources were used to examine hypothesized relations among neighborhood-, family-, and individual-level variables, and perceptions of neighborhood collective efficacy. Data were from 1,105 individuals (56% female, 42% African American, and 58% White) nested within 55 neighborhoods and 392 families, analyzed within a multilevel design using a 3-level model. At the neighborhood level, the study examined relations between Census, police, and neighborhood representative indicators. At the family level, the model examined the influence of marital status and family income. At the individual level, gender and age were examined. Results indicated that age at the individual level, marital status at the family level, and poverty and perceived gang activity at the neighborhood level predicted levels of neighborhood collective efficacy. The study illustrated significant variation across neighborhoods and families, and demonstrates the utility of combining different sources of neighborhood data to examine relations of interest within a multilevel framework.     

Modeling the Development of Children's Use of Optional Infinitives in Dutch and English Using MOSAIC

In this study we use a computational model of language learning called model of syntax acquisition in children (MOSAIC) to investigate the extent to which the optional infinitive (OI) phenomenon in Dutch and English can be explained in terms of a resource-limited distributional analysis of Dutch and English child-directed speech. The results show that the same version of MOSAIC is able to simulate changes in the pattern of finiteness marking in 2 children learning Dutch and 2 children learning English as the average length of their utterances increases. These results suggest that it is possible to explain the key features of the OI phenomenon in both Dutch and English in terms of the interaction between an utterance-final bias in learning and the distributional characteristics of child-directed speech in the 2 languages. They also show how computational modeling techniques can be used to investigate the extent to which cross-linguistic similarities in the developmental data can be explained in terms of common processing constraints as opposed to innate knowledge of universal grammar.     

A strategy-based interpretation of stroop

Most accounts of the Stroop effect (Stroop, 1935) emphasize its negative aspect, namely, that in particular situations, processing of an irrelevant stimulus dimension interferes with participants' performance of the instructed task. In contrast, this paper emphasizes the fact that, even with that interference, participants actually can (and usually do) exert enough control to perform the instructed task. An Adaptive Control of Thought–Rational (ACT–R) model of the Stroop task interprets this as a kind of learned strategic control. Specifically, the concept of utility is applied to the two processes that compete in the Stroop task, and a utility-learning mechanism serves to update the corresponding utility values according to experience and hence influence the competition. This model both accounts for various extant Stroop results and makes novel predictions about when people can reduce their susceptibility to Stroop interference. These predictions are tested in three experiments that involve a double-response variant of the Stroop task.     

Structure and strength in causal induction

We present a framework for the rational analysis of elemental causal induction-learning about the existence of a relationship between a single cause and effect-based upon causal graphical models. This framework makes precise the distinction between causal structure and causal strength: the difference between asking whether a causal relationship exists and asking how strong that causal relationship might be. We show that two leading rational models of elemental causal induction, DeltaP and causal power, both estimate causal strength, and we introduce a new rational model, causal support, that assesses causal structure. Causal support predicts several key phenomena of causal induction that cannot be accounted for by other rational models, which we explore through a series of experiments. These phenomena include the complex interaction between DeltaP and the base-rate probability of the effect in the absence of the cause, sample size effects, inferences from incomplete contingency tables, and causal learning from rates. Causal support also provides a better account of a number of existing datasets than either DeltaP or causal power.     

Generalized imitation within three response classes in typically developing infants

Effects of modeling and contingent praise on infant imitation of three different responses was analyzed. Generalization to nonreinforced probe models was assessed both within and across response types. Three 12- to 14-month-old infants and their mothers participated in this study. During baseline the mothers provided models only. During treatment mothers modeled and also praised contingent upon infant matching of the training models. During interspersed probe trials the mothers modeled different responses, which, if matched by the infant, produced no praise. The three responses modeled were motor-with-toy, motor-without-toy, and vocal responses. The dependent measure was the percentage of maternal models that were matched by the infant within 6 s. Nonmatching responses of the same response type were also measured. Results showed a systematic increase in the percentages of training and probe models matched by the three infants following the introduction of the model-and-praise treatment condition. Nonmatching responses did not systematically increase. Thus, imitation generalized within response class, but not across response classes.     

童年中晚期孤独感的发展轨迹：一项潜变量增长模型分析

使用问卷法和同伴提名法对884名小学二年级学生进行历时三年的四次追踪测试, 采用潜变量增长模型建模, 检验小学2~5年级学生孤独感的变化趋势, 并考察不同性别儿童孤独感变化的差异性以及同伴接纳对孤独感变化的影响。结果发现：(1) 2~5年级小学生孤独感呈曲线递减趋势, 递减速度逐渐减缓, 起始水平及发展速度均存在显著的个体差异; (2)女孩起始的孤独感水平显著低于男孩, 而发展速度、加速度则不存在显著的性别差异; (3)较高的同伴接纳对当时儿童孤独感的降低具有显著的促进作用。研究采用孤独感发展的情境观, 并结合儿童认知、自我发展的特点对结果进行了分析。     

A reappraisal of the relationship between span memory and intelligence via “best evidence synthesis”

This paper examines the relationship between span memory [e.g., immediate memory, short-term memory (STM), simple span] and general ability (g) though a reanalysis of two data sets [Christal, R. E. (1959). Factor analytic study of visual memory. Psychological Monographs: General and Applied, 72 (13, Whole No. 466); Kelley, H.P. (1964). Memory abilities: A factor analysis. Psychometric Monographs, No. 11]. Because of their large sample sizes and the multiple measures used to identify each construct, the Christal and Kelley studies were examined within a “best evidence synthesis” framework. Modern structural equation modeling (SEM) techniques were used to examine the relationship between immediate memory and g. Results indicated that in both studies, the relationship between immediate memory and g was quite substantial (.71 and .83), and that this relationship was essentially reduced by half when the common content variance of the tests was accounted for (e.g., verbal, spatial, numerical). Results are discussed within the context of recent research examining the relationship between working memory (WM) and g.     

A Latent Growth Curve Modeling Approach to Pooled Interrupted Time Series Analyses

This paper presents a latent variable approach for the estimation of treatment effects within a pooled interrupted time series (ITS) design. Although considered quasi-experimental, the ITS design has been noted as representing one of the strongest alternatives to the randomized experiment, making it highly appropriate for use in documenting the presence of effects that might warrant further evaluation in a large-scale randomized study. Results suggest that the latent variable growth modeling (LGM) is capable of detecting simultaneous differences in both level and slope, and provides tests of significance for these two necessary indicators of an ITS intervention effect. As shown in the analyses, the LGM framework provides a comprehensive and flexible approach to research design and data analysis, making available to a wide audience of researchers an analytical framework for a variety of analyses of growth and developmental processes.     

An evaluation of preference for video and in vivo modeling

We assessed preference for video or in vivo modeling using a concurrent-chains arrangement with 3 children with autism. The two modeling conditions produced similar acquisition rates and no differential selection (i.e., preference) for all 3 participants.     

The impact of parents, child care providers, teachers, and peers on early externalizing trajectories

This study utilized growth mixture modeling to examine the impact of parents, child care providers, teachers, and peers on the prediction of distinct developmental patterns of classroom externalizing behavior in elementary school. Among 241 children, three groups were identified. 84.6% of children exhibited consistently low externalizing behavior. The externalizing behavior of the Chronic High group (5.8%) remained elevated throughout elementary school; it increased over time in the Low Increasing group (9.5%). Negative relationships with teachers and peers in the kindergarten classroom increased the odds of having chronically high externalizing behavior. Teacher–child conflict increased the likelihood of a developmental pattern of escalating externalizing behavior. Boys were overrepresented in the behaviorally risky groups, and no sex differences in trajectory types were found.