On growth curves and mixture models

The multilevel model of change and the latent growth model are flexible means to describe all sorts of population heterogeneity with respect to growth and development, including the presence of sub‐populations. The growth mixture model is a natural extension of these models. It comes at hand when information about sub‐populations is missing and researchers nevertheless want to retrieve developmental trajectories from sub‐populations. We argue that researchers have to make rather strong assumptions about the sub‐populations or latent trajectory classes in order to retrieve existing population differences. A simulated example is discussed, showing that a sample of repeated measures drawn from two sub‐populations easily leads to the mistaken inference of three sub‐populations, when assumptions are not met. The merits of methodological advises on this issue are discussed. It is concluded that growth mixture models should be used with understanding, and offer no free way to growth patterns in unknown sub‐populations. Copyright © 2006 John Wiley & Sons, Ltd.     

大学生情绪智力和班级人际网络对适应性的影响机制:多层中介效应模型

以国内7所大学、20个教学班、646名学生为研究样本,采用问卷调查法和社会网络分析法收集数据。运用1-1-1中介效应模型分析大学生情绪智力、班级人际网络和适应性之间的关系。结果显示:(1)大学生适应性与情绪智力、班级人际网络的点度中心度呈显著正相关,情绪智力可正向预测大学生适应性,情绪智力可正向预测大学生在班级人际网络的点度中心度;(2)1-1-1中介效应模型分析结果显示班级人际网络的点度中心度在情绪智力与适应性关系中起部分中介作用。     

Being a good or a just teacher: Which experiences of teachers’ behavior can be more predictive of school bullying?

In two cross‐sectional questionnaire studies with N = 2,931 German students, aged between 12 and 17 years (M = 14.1, SD = 0.5), we investigated the relation between students’ bullying behavior and their personal belief in a just world (BJW). We considered students’ personal experience of teacher justice as a possible mediator in this relation and investigated whether the students’ experiences of their teachers’ classroom management explained bullying behavior in addition to personal BJW and teacher justice, while statistically controlling for sex and school type. In both studies, multilevel modeling results showed that the more students endorsed personal BJW and the more they evaluated their teachers’ behavior toward them personally as being just, the less likely they were to report that they bullied others. The students’ personal experience of teacher justice mediated the association of personal BJW with bullying. Furthermore, the students’ personal experience of classroom management significantly predicted bullying in addition to personal BJW and teacher justice. The observed relations were mainly significant at the individual level. The pattern of results persisted when we controlled for school type and when we considered student sex as a moderator. We discussed the adaptive functions of BJW and implications for future school research and practice.

     

纵向数据的调节效应分析

目前调节效应检验主要是基于截面数据, 本文讨论纵向(追踪)数据的调节效应分析。如果自变量X和因变量Y有纵向数据, 调节效应可分为三类：调节变量Z不随时间变化、Z随时间变化、调节变量从自变量或因变量中产生。评介了基于多层模型、多层结构方程模型、交叉滞后模型和潜变量增长模型的纵向数据的多种调节效应分析方法。调节效应的分解和潜调节结构方程法的使用是纵向数据的调节效应分析的两大特点。对基于四类模型的调节效应分析方法进行综合比较后, 总结出一个纵向数据的调节效应分析流程。随后用实际例子演示如何进行纵向数据的调节效应分析, 并给出相应的Mplus程序。随后展望了纵向数据的调节效应分析的拓展方向, 例如基于动态结构方程模型的密集追踪数据的调节效应分析。     

神经质人格对中小学生抑郁的影响：班级环境的跨层调节作用

基于素质-应激理论考察神经质人格及班级环境对中小学生抑郁的作用机制,对30个班级共933名中小学生进行问卷调查。多层分析结果显示：（1）中小学生抑郁存在显著的班级聚集效应;（2）神经质人格正向预测中小学生抑郁,班级人际环境、班级学习环境均负向预测中小学生抑郁;（3）班级学习环境跨层调节神经质人格与中小学生抑郁之间的关系,即积极的班级学习环境削弱了神经质人格对中小学生抑郁的影响。结果表明,我国教学制度下的班级学习环境在中小学生抑郁预防过程中可发挥重要作用。     

在线学习环境中教师幽默对学习投入的影响：一个多水平的结构方程分析

以教学幽默风格模型（Instructional Humor Styles）和教学幽默加工理论（Instructional Humor Processing Theory）为基础,通过构建多水平的结构方程模型探索在线学习环境中,教师幽默与学习投入关系。结果表明：（1）教师幽默与学习投入无显著相关;（2）在学生层面,仅学生感知的与课堂相关的教师幽默与学习投入呈显著正相关;（3）学生感知的与课堂相关,与课堂无关和攻击性的教师幽默均能通过积极情绪和消极情绪对学习投入产生影响。此外,自我贬低的教师幽默仅通过消极情绪对学习投入产生作用。本研究首次将教学幽默风格理论模型拓展至在线学习环境中,从教师层面和学生层面验证了该理论在我国的适应性。此外,本研究验证了教学幽默加工理论,揭示了教师幽默对学习投入的内在机制,这对改善在线学习环境中学生的学习投入具有一定的指导意义。     

The relationship between multilevel models and non‐parametric multilevel mixture models: Discrete approximation of intraclass correlation,random coefficient distributions,and residual heteroscedasticity

Multilevel data structures are common in the social sciences. Often, such nested data are analysed with multilevel models (MLMs) in which heterogeneity between clusters is modelled by continuously distributed random intercepts and/or slopes. Alternatively, the non‐parametric multilevel regression mixture model (NPMM) can accommodate the same nested data structures through discrete latent class variation. The purpose of this article is to delineate analytic relationships between NPMM and MLM parameters that are useful for understanding the indirect interpretation of the NPMM as a non‐parametric approximation of the MLM, with relaxed distributional assumptions. We define how seven standard and non‐standard MLM specifications can be indirectly approximated by particular NPMM specifications. We provide formulas showing how the NPMM can serve as an approximation of the MLM in terms of intraclass correlation, random coefficient means and (co)variances, heteroscedasticity of residuals at level 1, and heteroscedasticity of residuals at level 2. Further, we discuss how these relationships can be useful in practice. The specific relationships are illustrated with simulated graphical demonstrations, and direct and indirect interpretations of NPMM classes are contrasted. We provide an R function to aid in implementing and visualizing an indirect interpretation of NPMM classes. An empirical example is presented and future directions are discussed.     

基于多层结构方程模型的情境效应分析—— 兼与多层线性模型比较

多层(嵌套)数据的变量关系研究, 必须借助多层模型来实现。两层模型中, 层一自变量Xij按组均值中心化, 并将组均值 置于层2截距方程式中, 可将Xij对因变量Yij的效应分解为组间和组内部分, 二者之差被称为情境效应, 称为情境变量。多层结构方程模型(MSEM)将多层线性模型(MLM)和结构方程模型(SEM)相结合, 通过设置潜变量和多指标的方法校正了MLM在情境效应分析中出现的抽样误差和测量误差, 同时解决了数据的多层(嵌套)结构和潜变量的估计问题。除了分析原理的说明, 还以班级平均竞争氛围对学生竞争表现的情境效应为例进行分析方法的示范, 并比较MSEM和MLM的异同, 随后展望了MSEM情境效应模型、情境效应无偏估计方法和情境变量研究的拓展方向。     

Emotion and reason in everyday risk perception

Although research has documented the importance of emotion in risk perception, little is known about it in the context of everyday life. Using the Experience Sampling Method (ESM), 94 part‐time students were prompted at random—via cellular telephones—to report on mood state and three emotions and to assess risk on thirty occasions during their working hours. The emotions—valence, arousal, and dominance—were measured using self‐assessment manikins (SAMs) (Bradley & Lang, 1994). Hierarchical linear models (HLM) revealed that mood state and emotions explained significant variance in risk perception. In addition, valence and arousal accounted for variance over and above “reason” (measured by severity and possibility of risks). Six risks were re‐assessed in a post‐experimental session and found to be lower than their real‐time counterparts. The study demonstrates the feasibility and value of collecting representative samples of data with simple technology. Evidence is also provided to demonstrate the statistical consistency of the HLM estimates. Copyright © 2010 John Wiley & Sons, Ltd.     

腔内成形术治疗下肢动脉硬化闭塞症的技巧及临床观察

评价腔内成形术（PTA及PTAS）治疗下肢动脉硬化闭塞症的技巧和临床观察。2010年10月至2013年10月,对37例下肢动脉硬化闭塞症血管多段病变患者采用经皮血管腔内成形术和经皮血管腔内成形＋支架植入术治疗。结果36（97％）例手术成功,术后肢体缺血症状完全消失或明显改善,38条患肢皮温明显升高,间歇性跛行消失或距离延长,静息痛好转。术后踝／肱指数（ABI）（0．83±0．12）与术前（0．35±0．07）比较差异有统计学意义（P〈0．05）。合理的腔内成形术（PTA＋PTAS）是治疗下肢动脉硬化闭塞症安全有效的方法。熟练掌握腔内成形术是提高手术成功率和维持通畅率的关键。