Learning to Optimize Speed,Accuracy, and Energy Expenditure: A Framework for Understanding Speed-Accuracy Relations in Goal-Directed Aiming

Over the last century, investigators have developed a number of models to explain the relation between speed and accuracy in target-directed manual aiming. The models vary in the extent to which they stress the importance of feedforward processes and the online use of sensory information (see D. Elliott, W. F. Helsen, & R. Chua, 2001, for a recent review). A common feature of those models is that the role of practice in optimizing speed, accuracy, and energy expenditure in goal-directed aiming is either ignored or minimized. The authors present a theoretical framework for understanding speed-accuracy tradeoffs that takes into account the strategic, trial-to-trial behavior of the performer. The strategic behavior enables individuals to maximize movement speed while minimizing error and energy expenditure.     

At the Frontiers of Modeling Intensive Longitudinal Data: Dynamic Structural Equation Models for the Affective Measurements from the COGITO Study

With the growing popularity of intensive longitudinal research, the modeling techniques and software options for such data are also expanding rapidly. Here we use dynamic multilevel modeling, as it is incorporated in the new dynamic structural equation modeling (DSEM) toolbox in Mplus, to analyze the affective data from the COGITO study. These data consist of two samples of over 100 individuals each who were measured for about 100 days. We use composite scores of positive and negative affect and apply a multilevel vector autoregressive model to allow for individual differences in means, autoregressions, and cross-lagged effects. Then we extend the model to include random residual variances and covariance, and finally we investigate whether prior depression affects later depression scores through the random effects of the daily diary measures. We end with discussing several urgent—but mostly unresolved—issues in the area of dynamic multilevel modeling.     

Models for the statistics and mechanisms of response speed and accuracy

Van Breukelen offers a promising method for modeling both response speed and response accuracy. However, the underlying conception of both dependent measures is somewhat flawed, leading the author to conclude that the approach possesses limitations that, under revised assumptions, may not hold. The central misconception, and a set of related misconceptions, is addressed, and it is suggested that this approach holds a good deal of promise for application in the perceptual and cognitive sciences.     

Opportunities and Issues in Modeling Intensive Longitudinal Data: Learning from the COGITO Project

Abstract

Technological developments increasingly permit the collection of longitudinal data sets in which the data structure contains a large number of participants N and a large number of measurement occasions T. Promising new dynamical systems approaches to the analysis of large N, large T data sets have been proposed that utilize both between-subjects and within-subjects information. The COGITO project, begun over a decade ago, is an early large N?=?204, large T?=?100 study that collected high quality cognitive and psychosocial data. In this introduction, I describe the COGITO project and conceptual and statistical issues that arise in the analysis of large N, large T data sets. I provide a brief overview of the five papers in the special section which include conceptual pieces, a didactic presentation of a dynamic structural equation approach, and papers reporting new statistical analyses of the COGITO data set to answer substantive questions. Although many challenges remain, these new approaches offer the promise of improving scientific inquiry in the behavioral sciences.     

Person‐specific versus multilevel autoregressive models: Accuracy in parameter estimates at the population and individual levels

This paper compares the multilevel modelling (MLM) approach and the person‐specific (PS) modelling approach in examining autoregressive (AR) relations with intensive longitudinal data. Two simulation studies are conducted to examine the influences of sample heterogeneity, time series length, sample size, and distribution of individual level AR coefficients on the accuracy of AR estimates, both at the population level and at the individual level. It is found that MLM generally outperforms the PS approach under two conditions: when the sample has a homogeneous AR pattern, namely, when all individuals in the sample are characterized by AR processes with the same order; and when the sample has heterogeneous AR patterns, but a multilevel model with a sufficiently high order (i.e., an order equal to or higher than the maximum order of individual AR patterns in the sample) is fitted and successfully converges. If a lower‐order multilevel model is chosen for heterogeneous samples, the higher‐order lagged effects are misrepresented, resulting in bias at the population level and larger prediction errors at the individual level. In these cases, the PS approach is preferable, given sufficient measurement occasions (T ≥ 50). In addition, sample size and distribution of individual level AR coefficients do not have a large impact on the results. Implications of these findings on model selection and research design are discussed.     

A Comparison of Inverse-Wishart Prior Specifications for Covariance Matrices in Multilevel Autoregressive Models

Multilevel autoregressive models are especially suited for modeling between-person differences in within-person processes. Fitting these models with Bayesian techniques requires the specification of prior distributions for all parameters. Often it is desirable to specify prior distributions that have negligible effects on the resulting parameter estimates. However, the conjugate prior distribution for covariance matrices—the Inverse-Wishart distribution—tends to be informative when variances are close to zero. This is problematic for multilevel autoregressive models, because autoregressive parameters are usually small for each individual, so that the variance of these parameters will be small. We performed a simulation study to compare the performance of three Inverse-Wishart prior specifications suggested in the literature, when one or more variances for the random effects in the multilevel autoregressive model are small. Our results show that the prior specification that uses plug-in ML estimates of the variances performs best. We advise to always include a sensitivity analysis for the prior specification for covariance matrices of random parameters, especially in autoregressive models, and to include a data-based prior specification in this analysis. We illustrate such an analysis by means of an empirical application on repeated measures data on worrying and positive affect.     

Age and Sex Differences in Morningness/Eveningness Along the Life Span: A Cross-Sectional Study in Spain

Work psychology has noted the importance of considering the temporal dimension of behavior in organizations. Given that society widely operates on a 24-hr schedule, it is important to know how circadian typologies are distributed in the general population. In this study, diurnal preference was analyzed among 4,175 Spanish participants (61.3% women), 12–59 years old, who completed the Composite Scale of Morningness (Smith, Reilly, & Midkiff, 1989). Several measurement models of the CSM were analyzed using exploratory structural equation modeling and confirmatory factor analysis. The bifactor model showed the best fit, with a general factor (morningness/eveningness) and three subfactors (morningness, morning affect, and time of retiring). The age and sex factorial invariance of the bifactor model were tenable at the latent variance-covariance level. Next, age and sex differences analysis indicated a progressive increase in morningness with age, but over 40 years old, men were more morningness oriented than women were. These results indicate that morningness/eveningness can be considered a multidimensional construct and that psychosocial factors must be considered when estimating the prevalence of morningness/eveningness in different populations or countries.     

Age Differences in the Variance of Personality Characteristics

In contrast to mean‐level comparisons, age group differences in personality trait variance have received only passing research interest. This may seem surprising because individual differences in personality characteristics are exactly what most of personality psychology is about. Because different proposed mechanisms of personality development may entail either increases or decreases in variance over time, the current study is exploratory in nature. Age differences in variance were tested by comparing the standard deviations of the five‐factor model domain and facet scales across two age groups (20 to 30 years old versus 50 to 60 years old). Samples from three cultures (Estonia, the Czech Republic and Russia) were employed, and two methods (self‐reports and informant‐reports) were used. The results showed modest convergence across samples and methods. Age group differences were significant for 11 of 150 facet‐level comparisons but never consistently for the same facets. No significant age group differences were observed for the five‐factor model domain variance. Therefore, there is little evidence for individual differences in personality characteristics being systematically smaller or larger in older as opposed to younger people. We discuss the implications of these findings for understanding personality development. Copyright © 2015 European Association of Personality Psychology     

成人短时记忆发展的实验研究

以数字、图形和颜色为实验材料,测量了青年和老年被试在记忆广度和斯腾伯格任务中的成绩。结果表明随着年龄的增大,三种材料的记忆广度都有显著的下降,记忆的搜索速度也减慢;发现在老年期不同材料的记忆广度与搜索速度也存在反比例关系。作者认为这一结果对短时记忆容量发展研究具有重要意义并进行了进一步的讨论。     

Modeling Nonstationary Emotion Dynamics in Dyads using a Time-Varying Vector-Autoregressive Model

Emotion dynamics are likely to arise in an interpersonal context. Standard methods to study emotions in interpersonal interaction are limited because stationarity is assumed. This means that the dynamics, for example, time-lagged relations, are invariant across time periods. However, this is generally an unrealistic assumption. Whether caused by an external (e.g., divorce) or an internal (e.g., rumination) event, emotion dynamics are prone to change. The semi-parametric time-varying vector-autoregressive (TV-VAR) model is based on well-studied generalized additive models, implemented in the software R. The TV-VAR can explicitly model changes in temporal dependency without pre-existing knowledge about the nature of change. A simulation study is presented, showing that the TV-VAR model is superior to the standard time-invariant VAR model when the dynamics change over time. The TV-VAR model is applied to empirical data on daily feelings of positive affect (PA) from a single couple. Our analyses indicate reliable changes in the male’s emotion dynamics over time, but not in the female’s—which were not predicted by her own affect or that of her partner. This application illustrates the usefulness of using a TV-VAR model to detect changes in the dynamics in a system.     

Event rate and reaction time performance in ADHD: Testing predictions from the state regulation deficit hypothesis using an ex-Gaussian model

According to the state regulation deficit (SRD) account, ADHD is associated with a problem using effort to maintain an optimal activation state under demanding task settings such as very fast or very slow event rates. This leads to a prediction of disrupted performance at event rate extremes reflected in higher Gaussian response variability that is a putative marker of activation during motor preparation. In the current study, we tested this hypothesis using ex-Gaussian modeling, which distinguishes Gaussian from non-Gaussian variability. Twenty-five children with ADHD and 29 typically developing controls performed a simple Go/No-Go task under four different event-rate conditions. There was an accentuated quadratic relationship between event rate and Gaussian variability in the ADHD group compared to the controls. The children with ADHD had greater Gaussian variability at very fast and very slow event rates but not at moderate event rates. The results provide evidence for the SRD account of ADHD. However, given that this effect did not explain all group differences (some of which were independent of event rate) other cognitive and/or motivational processes are also likely implicated in ADHD performance deficits.     

Placing inspection time, reaction time, and perceptual speed in the broader context of cognitive ability: The VPR model in the Lothian Birth Cohort 1936

The idea that information processing speed is related to cognitive ability has a long history. Much evidence has been amassed in its support, with respect to both individual differences in general intelligence and developmental trajectories. Two so-called elementary cognitive tasks, reaction time and inspection time, have been used to compile this evidence, but most studies have used either one or the other. Relations between speed and fluid intelligence have tended to be stronger than those between speed and crystallized intelligence, but studies testing this have confounded verbal abilities with crystallized intelligence and spatial/perceptual abilities with fluid intelligence. Questions have also been raised regarding whether speed contributes directly to general intelligence or to more specific cognitive abilities to which general intelligence also contributes. We used 18 ability and speed measures in the Lothian Birth Cohort 1936, assessed at approximately age 70, to construct alternative versions of the Verbal-Perceptual-Image Rotation (Johnson & Bouchard, 2005a) model of cognitive ability to test different hypotheses regarding these issues. Though differences in the extents to which our models fit the data were relatively small, they suggested that reaction and inspection time tasks were comparable indicators of information processing speed with respect to general intelligence, that verbal and spatial abilities were similarly related to information processing speed, and that spatial, verbal, and perceptual speed abilities were more directly related to information processing speed than was general intelligence. We discuss the theoretical implications of these results.     

项目分值对学习时间分配的影响：一种动态的过程

摘 要 研究考察了不同学习时段上,项目分值对学习时间分配的影响。结果发现: (1)分值的主效应显著,被试会选择更多的高分值项目学习, 且在高分值项目上分配更多的学习时间; (2)分值与学习时段存在交互作用,被试首先学习高分值项目,随后逐渐将学习重心转向中等分值项目,最后在临近测试前重点重学高分值项目。结果表明：学习时间分配是动态变化的,个体为了尽可能实现学习目标会在学习过程中不断调整所建构的议程。     

Testing for Granger Causality in the Frequency Domain: A Phase Resampling Method

This article introduces phase resampling, an existing but rarely used surrogate data method for making statistical inferences of Granger causality in frequency domain time series analysis. Granger causality testing is essential for establishing causal relations among variables in multivariate dynamic processes. However, testing for Granger causality in the frequency domain is challenging due to the nonlinear relation between frequency domain measures (e.g., partial directed coherence, generalized partial directed coherence) and time domain data. Through a simulation study, we demonstrate that phase resampling is a general and robust method for making statistical inferences even with short time series. With Gaussian data, phase resampling yields satisfactory type I and type II error rates in all but one condition we examine: when a small effect size is combined with an insufficient number of data points. Violations of normality lead to slightly higher error rates but are mostly within acceptable ranges. We illustrate the utility of phase resampling with two empirical examples involving multivariate electroencephalography (EEG) and skin conductance data.     

Personality Development in Emerging and Young Adulthood: A Study of Age Differences

Early adulthood is a time of substantial personality change characterized by large inter‐individual diversity. To investigate the role of age in this diversity, the present study examined whether emerging adults differ from an older group of young adults in their Big Five personality development. By means of multi‐group latent change modelling, two groups of 16‐ to 19‐year‐olds (n = 3555) and 26‐ to 29‐year‐olds (n = 2621) were tracked over the course of four years and compared regarding four aspects of personality change: mean‐level change, rank‐order change, inter‐individual differences in change, and profile change. In addition, age‐differential socialization effects associated with six first‐time life events were investigated. Analyses revealed substantial age differences in all four aspects of change. As expected, emerging adults showed greater change and diversity in change than young adults. However, the six life events had no age‐differential impact on change in single traits and Big Five profiles. Overall, the results indicate that age differences should be considered even in specific life stages to advance the understanding of personality development. © 2018 European Association of Personality Psychology     

成人期智力的年龄特征：中美比较研究

西方成人期心理发展方面的追踪研究积累了有关成人智力年龄变化模式的重要资料。非西方国家这方面的资料却非常少,因而也就无从得知非西方国家成人智力年龄差异和增龄模式是与此相似还是相异。通过成人期智力发展的跨文化研究,可以了解不同文化背景下智力变化和代际差异的一般规律。本研究旨在探究社会变迁和文化背景会对成人的智力发展产生怎样的影响。     

Creative at Each Age: Age‐Related Differences in Drivers of Workplace Creativity from an Experience Sampling Study

Creativity and innovation are essential agents for change processes and accelerating technical development. Having to face challenges, such as demographic change, organizations require individuals who are creative and innovative at each age. Previous research identified affect as a crucial determinant of creativity, even though empirical findings showed inconsistencies. Drawing on literature on age‐related changes in affective experiences, we investigated the moderating effect of employees’ age on the association between daily positive and negative affect and creativity using a daily diary study. A total of 116 employees responded to daily questionnaires twice a day over five consecutive working days. As expected, hierarchical linear modeling analyses revealed differential effects regarding the affect‐creativity association, dependent on employees’ age. Although older employees were most creative on days when they experienced a high level of positive affect (compared to their mean level of positive affect), younger employees were particularly creative when experiencing negative affect (compared to their mean level of negative affect). We discuss practical implications on how organizations could provide creativity‐enhancing work environments for employees at each age.     

Gender Differences in Fat Talk Among American Adults: Results from the Psychology of Size Survey

Vignettes were used to assess gender differences in likelihood of hearing others engage in and perceived pressure to join in positive, negative (fat talk), and self-accepting body talk. An age-representative sample of 4,014 adult women and men voluntarily responded to an emailed “Health and Wellness” survey from an internet polling company with whom they had pre-registered. Women reported more likelihood of hearing fat-talk scenarios and greater pressure to participate in them compared to men. Only a subset of participants reported frequent exposure to and pressure to join in fat talk. Demographic predictors of pressure to engage in fat talk were also examined. This was the first survey to examine body talk among older adults.     

A Study of Gender Differences in Autobiographical Memory: Broken Down by Age and Sex

Data from 40 older adults who produced autobiographical memories to word cues and to the request to list five important memories, and data from 60 older adults who answered factual multiple-choice questions for events spread across their lives, were analyzed for gender differences. In spite of considerable statistical power, there were no gender differences in the distribution of autobiographical memories over the lifespan, in the distribution of important memories, in various ratings provided to these memories, or in the distribution of knowledge for events. The only gender difference found was that men performed better on factual questions about current events and baseball. Thus, counter to what might be expected from Darwinian theory and some behavioral data, gender differences were minimal.