多阶段混合增长模型的影响因素：距离与形态

通过模拟研究, 考察潜类别距离和发展形态等因素对多阶段混合增长模型的模型选择和参数估计的影响：(1)潜类别距离越大, 模型选择和分类效果越好。(2)混合模型的选择, 应以一定样本量(至少200)为前提, 首先考虑BIC选出正确的分类模型, 再通过熵值、ARI等选择分类确定性较高的模型。(3)多阶段的发展形态对正确模型的选择和分类的确定性均有一定程度影响。(4)潜类别距离和样本量越大, 参数估计精度越高。(5)在判断分类准确性的指标中, ARI的选择更偏向于真实的模型。     

类别数量对基于规则和信息整合类别学习的影响

研究以大学生为被试,运用即时反馈训练范式,探讨类别数量对基于规则和信息整合两种结构的类别学习的影响,并探讨被试在类别学习过程中的反应策略。实验结果显示:(1)类别数量不仅影响基于规则结构的类别学习,也影响信息整合结构的类别学习,类别学习成绩随类别数量的增多而下降;(2)在基于规则类别学习中,大多数被试使用理想的分类规则进行类别判断;在信息整合类别学习中,大多数被试使用极端值策略。研究结果支持难度观,不支持多重系统理论。     

时变效应模型及在密集追踪数据分析中的应用

密集追踪数据通常蕴含了心理过程的详细变化信息,反映了某些心理的复杂变化过程。时变效应模型用函数替代恒定的系数,可描述密集追踪数据中随时间推移心理的动态变化过程和时变效应,是分析复杂心理过程的有效方法。在介绍时变效应模型的原理后,通过模拟研究考察模型的表现,结果显示:(1)样本量增加可降低函数估计的误差;(2)惩罚样条法的节点数选择与函数的复杂度有关,函数越复杂,所需节点越多;(3)样本量与节点数对函数估计误差的交互效应不显著。进一步应探讨测量次数、数据分布形态、数据缺失等如何影响模型的表现。     

反馈延迟对信息整合类别学习的影响：视觉项目精确性的调节作用

研究旨在探究更精确的视觉项目表征能否消除延迟反馈对信息整合学习的损害。实验采用2(视觉项目表征精确性:精确/非精确)×2(反馈延迟:即时反馈/延迟反馈)组间设计,结果发现无论有无延迟反馈,精确的项目表征条件下类别学习成绩都显著高于非精确条件,精确性与反馈延迟存在交互作用。采用状态痕迹分析进一步证明精确性显著影响信息整合类别学习的稳定性。在反馈延迟条件下,精确的视觉项目表征能提高信息整合类别学习的成绩。     

因果关系及典型性程度对类别特征推理的影响

采用学习―测试二阶段实验范式,探讨了因果关系及典型性程度对类别特征推理的影响。研究结果表明:(1)因果关系影响类别特征推理任务;(2)典型性程度影响类别特征推理任务;(3)类别特征间存在因果关系的前提下,原因特征维度值与典型性程度间存在交互作用。典型性程度对不含原因特征的项目的特征推理影响是有限的。     

内源性注意和外源性注意条件下SOA变化对数字距离效应的影响

采用内源性注意和外源性注意实验范式,材料为小数(1～4)和大数(6～9)的阿拉伯数字,以判断数字是否大于5为任务,考察内源性和外源性线索不同注意条件下SOA对数字距离效应的影响。结果发现:(1)内源性线索条件下,随着SOAs增加,大小数的距离效应逐渐增大,当SOA为900ms时,大小数的距离效应最明显;(2)外源性线索条件下,当SOA为300ms时,大小数的距离效应最显著,随着SOAs增加,大小数的距离效应逐渐减小。     

身体意象可塑吗?——同步性和距离参照系对身体拥有感的影响

身体意象是个体在意识层面对与身体有关的知觉、态度及信念,它的稳定性与可塑性一直存在争论。本研究使用方位追踪仪、数据手套及投影仪,通过2个实验考查虚拟手错觉中距离参照系对身体拥有感的影响。实验1在虚拟环境中采用经典橡胶手错觉的变式,考察同步性和虚拟手位置对拥有感的影响;实验2引入距离参照系,考察在不同参照条件下被试对同一个位置的虚拟手在不同同步情况下的拥有感错觉。研究结果发现:(1)无论是同步性还是距离都会对虚拟手错觉中的拥有感产生影响,即同步比不同步条件下、距离近比距离远条件下拥有感显著;(2)不同的距离参照系对同一位置的拥有感体验影响差异显著,先近后远的呈现方式会减弱错觉而先远后近的呈现方式则会加强错觉。这一发现与身体拥有感是受稳定的身体意象调节的假设并不一致。     

继时呈现条件下类别归纳过程的ERPs研究

采用ERP技术对继时呈现条件下类别归纳过程进行了实验研究.使用几何图形为材料,18名被试在单维属性不告知、单维属性告知、双维属性不告知三种条件下完成类别归纳任务.通过对相关ERP成分的分析得出以下结论:(1)在继时呈现归纳材料的情况下,对刺激的加工是在已有背景基础上对后来呈现的刺激进行选择性加工,从而形成类别;(2)成年人与儿童在类别归纳中认知加工方式可能存在不同,当类别归纳的复杂程度增加时,即在需要归纳的属性从一个变为两个的时候,成年人仍然倾向于通过归纳出类别判断规则用于分类任务,而非通过相似性进行判断;(3)继时呈现材料条件下类别归纳任务中出现的P400可能是标志类别归纳过程完成的ERP成分,而且与对刺激属性加工具体过程无关.     

物质成瘾领域延迟折扣研究中的外部效度问题

物质成瘾者的跨期决策缺陷已被大量使用金钱延迟折扣任务的研究所证实。然而近年来, 来自金钱延迟折扣任务变式(成瘾物质延迟折扣任务、性延迟折扣任务和跨类别延迟折扣任务)的发现表明, 在物质成瘾领域的延迟折扣研究中单一使用金钱延迟折扣任务存在一定的局限性。首先, 物质成瘾者对金钱的延迟折扣水平可能并不能完全代表其对成瘾物质、性和其它自然奖赏的延迟折扣水平; 其次, 仅使用单一延迟折扣任务可能存在对物质成瘾者跨期决策过程的过度简化; 最后, 金钱延迟折扣任务较其变式对物质成瘾者的一些临床特征不够敏感。未来研究应进一步丰富、拓展物质成瘾领域的跨类别延迟折扣研究, 并对可能影响跨期决策的时间因素进行深入探索。     

工作记忆容量与内容相关性对类别学习的影响

类别学习是通过不断地分类练习,学会如何将类别刺激进行归类的过程。采用2(工作记忆容量:高、低)×4(内容相关性:方向、宽度、亮度、控制组)被试间实验设计,通过两个实验探讨工作记忆容量与内容相关性对基于规则类别学习和信息整合类别学习的影响。结果显示:(1)对基于规则类别学习来说,在高工作记忆容量条件下,当关注相关维度时,类别学习的成绩更好;(2)对基于信息整合类别学习来说,不管工作记忆容量如何,只要关注相关维度类别学习的成绩更好。     

A comparison of latent trait and latent class analyses of Likert-type data

This paper brings together and compares two developments in the analysis of Likert attitude scales. The first is the generalization of latent class models to ordered response categories. The second is the introduction of latent trait models with multiplicative parameter structures for the analysis of rating scales. Key similarities and differences between these two methods are described and illustrated by applying a latent trait model and a latent class model to the analysis of a set of life satisfaction data. The way in which the latent trait model defines a unit of measurement, takes into account the order of the response categories, and scales the latent classes, is discussed. While the latent class model provides better fit to these data, this is achieved at the cost of a logically inconsistent assignment of individuals to latent classes.The author wishes to thank Clifford C. Clogg, Otis Dudley Duncan and Benjamin D. Wright for their helpful comments on an earlier version of this paper.     

Spurious Latent Class Problem in the Mixed Rasch Model: A Comparison of Three Maximum Likelihood Estimation Methods under Different Ability Distributions

Recent research has shown that over-extraction of latent classes can be observed in the Bayesian estimation of the mixed Rasch model when the distribution of ability is non-normal. This study examined the effect of non-normal ability distributions on the number of latent classes in the mixed Rasch model when estimated with maximum likelihood estimation methods (conditional, marginal, and joint). Three information criteria fit indices (Akaike information criterion, Bayesian information criterion, and sample size adjusted BIC) were used in a simulation study and an empirical study. Findings of this study showed that the spurious latent class problem was observed with marginal maximum likelihood and joint maximum likelihood estimations. However, conditional maximum likelihood estimation showed no overextraction problem with non-normal ability distributions.     

Assessing the Robustness of Mixture Models to Measurement Noninvariance

Abstract

Recent work reframes direct effects of covariates on items in mixture models as differential item functioning (DIF) and shows that, when present in the data but omitted from the fitted latent class model, DIF can lead to overextraction of classes. However, less is known about the effects of DIF on model performance—including parameter bias, classification accuracy, and distortion of class-specific response profiles—once the correct number of classes is chosen. First, we replicate and extend prior findings relating DIF to class enumeration using a comprehensive simulation study. In a second simulation study using the same parameters, we show that, while the performance of LCA is robust to the misspecification of DIF effects, it is degraded when DIF is omitted entirely. Moreover, the robustness of LCA to omitted DIF differs widely based on the degree of class separation. Finally, simulation results are contextualized by an empirical example.     

青少年早期同伴侵害的亚类别及其稳定性:个体定向的分析

以山东省济南市12所初中的2015名初一学生为被试,对其持续追踪至初二年级,采用自我报告法测查青少年的同伴侵害、受欺负和社交退缩,采用同伴提名法测查青少年的攻击行为。采用潜在剖面分析和潜在转变分析,探讨青少年早期同伴侵害的亚类别以及各亚类别中青少年受侵害身份的稳定性与发展变化。结果发现：（1）同伴侵害亚类别可以分为：未受侵害组、低受侵害组、中等受侵害组和高受侵害组四类,各亚类别间的异质性主要体现在受侵害程度上;（2）中等受侵害组和高受侵害组表现出高水平的攻击行为和社交退缩,且高受侵害组的社交退缩行为更多;（3）青少年早期个体的受侵害身份具有中到高水平的稳定性,同时也存在着一定的发展变化,主要表现为高受侵害组青少年倾向于向中等受侵害组转变,中等受侵害组青少年倾向于向低受侵害组转变。攻击行为是受侵害身份转变的重要预测因素。     

回归混合模型：方法进展与软件实现

近来以个体为分析对象的方法日益受到研究者的重视, 其中潜类别和潜剖面模型最为流行。研究者在潜类别和潜剖面模型建模时往往需要进一步探讨协变量与潜分组之间的关系(即带有协变量的潜类别模型)。例如, 哪些变量预测个体类别归属, 以及个体的类别归属对结果变量的预测。本文对近年来研究者提出的各种方法进行了回顾和比较。包括当结果变量是分类变量的LTB法; 当结果变量是连续变量时的BCH和稳健三步法。在此基础上, 文章为应用研究者提供了Mplus软件示例, 并在最后对当前研究存在的问题和未来研究趋势进行了简要评价。     

A Person‐Centered Examination of Adolescent Religiosity Using Latent Class Analysis

Empirical studies of religion's role in society, especially those focused on individuals and analyzing survey data, conceptualize and measure religiosity as ranging from low to high on a single measure or a summary index of multiple measures. Other concepts, such as “lived religion,” “believing without belonging,” or “fuzzy fidelity” emphasize what scholars have noted for decades: humans are rarely consistently low, medium, or high across dimensions of religiosity including institutional involvement, private practice, salience, or belief. A method with great promise for identifying population patterns in how individuals combine types and levels of belief, practice, and personal religious salience is latent class analysis. In this article, we use data from the first wave of the National Study of Youth and Religion's telephone survey to discuss how to select indicators of religiosity in an informed manner, as well as the implications of the number and types of indicators used for model fit. We identify five latent classes of religiosity among adolescents in the United States and their sociodemographic correlates. Our findings highlight the value of a person‐centered approach to understanding how religion is lived by American adolescents.     

潜在类别分析技术在心理学研究中的应用

潜在类别分析是通过对类别型的外显变量和潜在变量之间的关系建立统计模型,根据模型参数得到各种潜在类别的具体外在表现的潜在特征分类技术。该分析方法主要应用于心理行为特征的分类、控制认知心理实验中被试个体差异引起的系统误差、评价临床心理诊断的精确性,以及心理测验中的项目分析、信度分析、结构分析等。对此方法的优劣进行分析比较,表明:该方法可以与其他测量理论相结合进一步拓展其在心理测量中的应用,也可在纵向数据和多水平数据中应用。在应用中亦有提升方法技术的空间。     

Using latent class analysis to identify aggressors and victims of peer harassment

This study used latent class analysis (LCA) to identify and classify individuals into aggressor and victim latent classes. Participants were over 2,000 sixth grade students who completed peer nomination procedures that identified students who had reputations as perpetrators and/or victims of physical, verbal, or relational harassment. Results showed five latent classes. Consistent with previous research, LCA identified latent classes of victims, aggressors, and socially adjusted students. However, rather than a single aggressive-victim subgroup, LCA identified latent classes of highly-victimized aggressive-victims and highly-aggressive aggressive-victims. Comparisons showed differences in mean profiles and classification criteria between LCA and traditional dichotomization approaches. Adjustment outcomes showed that highly-victimized aggressive-victims generally experienced greater negative psychological and social adjustment outcomes than highly-aggressive aggressive-victims. Implications of these findings for better assessment of victim and aggressor subgroups were discussed.     

Uncovering Substantive Patterns in Student Responses in International Large-Scale Assessments—Comparing a Latent Class to a Manifest DIF Approach

In this study, we contrast results from two differential item functioning (DIF) approaches (manifest and latent class) by the number of items and sources of items identified as DIF using data from an international reading assessment. The latter approach yielded three latent classes, presenting evidence of heterogeneity in examinee response patterns. It also yielded more DIF items with larger effect sizes and more consistent item response patterns by substantive aspects (e.g., reading comprehension processes and cognitive complexity of items). Based on our findings, we suggest empirically evaluating the homogeneity assumption in international assessments because international populations cannot be assumed to have homogeneous item response patterns. Otherwise, differences in response patterns within these populations may be under-detected when conducting manifest DIF analyses. Detecting differences in item responses across international examinee populations has implications on the generalizability and meaningfulness of DIF findings as they apply to heterogeneous examinee subgroups.