Methodology: European Journal of Research Methods for The Behavioral and Social Sciences最新文献

英文中文

Multicollinearity and missing constraints: A comparison of three approaches for the analysis of latent nonlinear effects. 多重共线性与缺失约束:分析潜在非线性效应的三种方法的比较。

IF 3.1 3区心理学 Q2 PSYCHOLOGY, MATHEMATICAL

Methodology: European Journal of Research Methods for The Behavioral and Social Sciences

Pub Date : 2008-05-07 DOI: 10.1027/1614-2241.4.2.51

A. Kelava, H. Moosbrugger, Polina Dimitruk, K. Schermelleh-engel

Multicollinearity complicates the simultaneous estimation of interaction and quadratic effects in structural equation modeling (SEM). So far, approaches developed within the Kenny-Judd (1984) tradition have failed to specify additional and necessary constraints on the measurement error covariances of the nonlinear indicators. Given that the constraints comprise, in part, latent linear predictor correlations, multicollinearity poses a problem for such approaches. Klein and Moosbrugger’s (2000) latent moderated structural equations approach (LMS) approach does not utilize nonlinear indicators and should therefore not be affected by this problem. In the context of a simulation study, we varied predictor correlation and the number of nonlinear effects in order to compare the performance of three approaches developed for the estimation of simultaneous nonlinear effects: Ping’s (1996) two-step approach, a correctly extended Joreskog-Yang (1996) approach, and LMS. Results show that in contrast to the Joreskog-Ya...

多重共线性使结构方程建模中相互作用和二次效应的同时估计变得复杂。到目前为止，在Kenny-Judd(1984)传统中开发的方法未能指定非线性指标的测量误差协方差的额外和必要的约束。考虑到约束部分包括潜在线性预测相关性，多重共线性给这种方法带来了问题。Klein和Moosbrugger(2000)的潜在调节结构方程方法(LMS)方法不使用非线性指标，因此不应该受到这个问题的影响。在模拟研究的背景下，我们改变了预测因子的相关性和非线性效应的数量，以便比较用于同时估计非线性效应的三种方法的性能:Ping(1996)的两步方法，正确扩展的Joreskog-Yang(1996)方法和LMS。结果表明，与Joreskog-Ya相比，…

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引用次数: 59

Effect of the Number of Response Categories on the Reliability and Validity of Rating Scales 反应类别数对评定量表信度效度的影响

IF 3.1 3区心理学 Q2 PSYCHOLOGY, MATHEMATICAL

Methodology: European Journal of Research Methods for The Behavioral and Social Sciences

Pub Date : 2008-05-07 DOI: 10.1027/1614-2241.4.2.73

Luis M. Lozano, E. García-Cueto, J. Muñiz

The Likert-type format is one of the most widely used in all types of scales in the field of social sciences. Nevertheless, there is no definitive agreement on the number of response categories that optimizes the psychometric properties of the scales. The aim of the present work is to determine in a systematic fashion the number of response alternatives that maximizes the fundamental psychometric properties of a scale: reliability and validity. The study is carried out with data simulated using the Monte Carlo method. We simulate responses to 30 items with correlations between them ranging from 0.2 to 0.9. We also manipulate sample size, analyzing four different sizes: 50, 100, 200, and 500 cases. The number of response options employed ranges from two to nine. The results show that as the number of response alternatives increases, both reliability and validity improve. The optimum number of alternatives is between four and seven. With fewer than four alternatives the reliability and validity decrease, an...

李克特量表是社会科学领域中应用最广泛的量表之一。然而，对于优化量表的心理测量特性的反应类别的数量并没有明确的共识。本研究的目的是以一种系统的方式确定能最大限度地发挥量表的基本心理测量特性的反应选项的数量:信度和效度。利用蒙特卡罗方法模拟数据进行了研究。我们模拟了对30个项目的反应，它们之间的相关性从0.2到0.9不等。我们还处理了样本量，分析了四种不同的样本量:50、100、200和500例。所采用的回答选项的数量从2到9不等。结果表明，随着选项数的增加，信度和效度都有所提高。选择的最佳数量在4到7之间。当备选方案少于4个时，信度和效度就会下降。

引用次数: 623

Longitudinal Data Analysis with Structural Equations 结构方程纵向数据分析

IF 3.1 3区心理学 Q2 PSYCHOLOGY, MATHEMATICAL

Methodology: European Journal of Research Methods for The Behavioral and Social Sciences

Pub Date : 2008-01-21 DOI: 10.1027/1614-2241.4.1.37

J. Rosel, I. Plewis

Abstract. In this paper we review different structural equation models for the analysis of longitudinal data: (a) univariate models of observable variables, (b) multivariate models of observable variables, (c) models with latent variables, (d) models that are unconditioned or conditioned to other variables (depending on the variability of the independent variables: time-varying or time-invariant, and depending on the type of independent variables: of latent variables or of observable variables), (e) models with interaction of variables, (f) models with nonlinear variables, (g) models with a constant, (h) with single level and multilevel measurement, and (i) other advances in SEM of longitudinal data (latent growth curve model, latent difference score, etc.). We pay more attention to the interaction of variables and to nonlinear transformations of variables because they are not frequently used in empirical investigation. They do, however, offer interesting possibilities to researchers who wish to verify re...

摘要在本文中，我们回顾了用于纵向数据分析的不同结构方程模型:(a)可观察变量的单变量模型，(b)可观察变量的多变量模型，(c)具有潜在变量的模型，(d)无条件或条件于其他变量的模型(取决于自变量的可变性:时变或时不变，以及取决于自变量的类型)。(e)变量相互作用模型，(f)非线性变量模型，(g)常数模型，(h)单水平和多水平测量模型，以及(i)纵向数据SEM的其他进展(潜在增长曲线模型，潜在差异评分等)。我们更关注变量的相互作用和变量的非线性变换，因为它们在实证研究中不常用。然而，它们确实为希望验证re的研究人员提供了有趣的可能性。

引用次数: 31

Factorial Invariance and The Specification of Second-Order Latent Growth Models. 阶乘不变性与二阶潜在增长模型的规范。

IF 2 3区心理学 Q2 PSYCHOLOGY, MATHEMATICAL

Methodology: European Journal of Research Methods for The Behavioral and Social Sciences

Pub Date : 2008-01-01 DOI: 10.1027/1614-2241.4.1.22

Emilio Ferrer, Nekane Balluerka, Keith F Widaman

Latent growth modeling has been a topic of intense interest during the past two decades. Most theoretical and applied work has employed first-order growth models, in which a single manifest variable serves as indicator of trait level at each time of measurement. In the current paper, we concentrate on issues regarding second-order growth models, which have multiple indicators at each time of measurement. With multiple indicators, tests of factorial invariance of parameters across times of measurement can be tested. We conduct such tests using two sets of data, which differ in the extent to which factorial invariance holds, and evaluate longitudinal confirmatory factor, latent growth curve, and latent difference score models. We demonstrate that, if factorial invariance fails to hold, choice of indicator used to identify the latent variable can have substantial influences on the characterization of patterns of growth, strong enough to alter conclusions about growth. We also discuss matters related to the scaling of growth factors and conclude with recommendations for practice and for future research.

在过去的二十年里，潜在增长模型一直是一个备受关注的话题。大多数理论和应用工作都采用一阶增长模型，其中单个表现变量在每次测量时作为特征水平的指标。在本文中，我们主要关注二阶增长模型的问题，二阶增长模型在每次测量时都有多个指标。使用多个指标，可以测试参数在测量时间上的因子不变性。我们使用两组数据进行这样的测试，这两组数据在因子不变性的程度上有所不同，并评估纵向验证因素、潜在增长曲线和潜在差异评分模型。我们证明，如果因子不变性不能成立，用于识别潜在变量的指标的选择可以对增长模式的表征产生实质性影响，足以改变关于增长的结论。我们还讨论了与生长因子比例相关的问题，并总结了对实践和未来研究的建议。

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引用次数: 0

Model error in covariance structure models: Some implications for power and Type I error. 协方差结构模型中的模型误差：对功率和I型误差的一些启示。

IF 2 3区心理学 Q2 PSYCHOLOGY, MATHEMATICAL

Methodology: European Journal of Research Methods for The Behavioral and Social Sciences

Pub Date : 2008-01-01 DOI: 10.1027/1614-2241.4.4.159

Donna L Coffman

The present study investigated the degree to which violation of the parameter drift assumption affects the Type I error rate for the test of close fit and power analysis procedures proposed by MacCallum, Browne, and Sugawara (1996) for both the test of close fit and the test of exact fit. The parameter drift assumption states that as sample size increases both sampling error and model error (i.e. the degree to which the model is an approximation in the population) decrease. Model error was introduced using a procedure proposed by Cudeck and Browne (1992). The empirical power for both the test of close fit, in which the null hypothesis specifies that the Root Mean Square Error of Approximation (RMSEA) ≤ .05, and the test of exact fit, in which the null hypothesis specifies that RMSEA = 0, is compared with the theoretical power computed using the MacCallum et al. (1996) procedure. The empirical power and theoretical power for both the test of close fit and the test of exact fit are nearly identical under violations of the assumption. The results also indicated that the test of close fit maintains the nominal Type I error rate under violations of the assumption.

本研究调查了参数漂移假设的违反程度对密切拟合测试和MacCallum， Browne和Sugawara（1996）提出的密切拟合测试和精确拟合测试的功率分析程序的I型错误率的影响程度。参数漂移假设表明，随着样本量的增加，抽样误差和模型误差（即模型在总体中近似的程度）都会减小。采用Cudeck和Browne（1992）提出的程序引入模型误差。近拟合检验（零假设规定近似均方根误差(RMSEA)≤0.05）和精确拟合检验（零假设规定RMSEA = 0）的经验功率与使用MacCallum等人（1996）程序计算的理论功率进行比较。在不符合假设的情况下，接近拟合检验和精确拟合检验的经验幂和理论幂几乎相同。结果还表明，在违反假设的情况下，密切拟合检验保持名义I型错误率。

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引用次数: 0

Challenges in Nonlinear Structural Equation Modeling 非线性结构方程建模的挑战

IF 3.1 3区心理学 Q2 PSYCHOLOGY, MATHEMATICAL

Methodology: European Journal of Research Methods for The Behavioral and Social Sciences

Pub Date : 2007-09-27 DOI: 10.1027/1614-2241.3.3.100

Polina Dimitruk, K. Schermelleh-engel, A. Kelava, H. Moosbrugger

Abstract. Challenges in evaluating nonlinear effects in multiple regression analyses include reliability, validity, multicollinearity, and dichotomization of continuous variables. While reliability and validity issues are solved by employing nonlinear structural equation modeling, multicollinearity remains a problem which may even be aggravated when using latent variable approaches. Further challenges of nonlinear latent analyses comprise the distribution of latent product terms, a problem especially relevant for approaches using maximum likelihood estimation methods based on multivariate normally distributed variables, and unbiased estimates of nonlinear effects under multicollinearity. The only methods that explicitly take the nonnormality of nonlinear latent models into account are latent moderated structural equations (LMS) and quasi-maximum likelihood (QML). In a small simulation study both methods yielded unbiased parameter estimates and correct estimates of standard errors for inferential statistic...

摘要评估多元回归分析中非线性效应的挑战包括信度、效度、多重共线性和连续变量的二分类。虽然采用非线性结构方程模型解决了信度和效度问题，但多重共线性仍然是一个问题，使用潜变量方法甚至可能加剧多重共线性问题。非线性潜在分析的进一步挑战包括潜在乘积项的分布，这是一个特别与基于多变量正态分布变量的最大似然估计方法相关的问题，以及多重共线性下非线性效应的无偏估计。明确考虑非线性潜在模型的非正态性的方法只有潜在调节结构方程(LMS)和拟极大似然(QML)。在一个小型模拟研究中，这两种方法都得到了无偏参数估计和正确的推断统计标准误差估计。

引用次数: 103

Visualizing Multivariate Dependencies with Association Chain Graphs 用关联链图可视化多变量依赖关系

IF 3.1 3区心理学 Q2 PSYCHOLOGY, MATHEMATICAL

Methodology: European Journal of Research Methods for The Behavioral and Social Sciences

Pub Date : 2007-03-09 DOI: 10.1027/1614-2241.3.1.24

M. Höfler, T. Brückl, A. Bittner, R. Lieb

In a recent paper, a new type of graph to visualize the results from graphical models was proposed. Association chain graphs (ACGs) provide a richer visualization than conventional graphs (directed acyclic and recursive regression graphs) if the data can be described with only a small number of parameters. ACGs display not only which associations reach statistical significance, but also the magnitude of associations (confidence intervals for statistical main effects) as the contrast color to the background color of the graph. In this paper, the ACG visualization is extended especially for the case where all variables are binary by illustrating their relative frequencies. This shows the degrees of associations not only on the individual (as expressed by odds ratios or other indexes of association) but also on the community level. We applied the approach to an extensive example of birth and childhood factors for the onset of affective mental disorders using data from the EDSP (Early Developmental Stages of ...

在最近的一篇论文中，提出了一种新的图形来可视化图形模型的结果。关联链图(acg)提供了比传统图(有向无环图和递归回归图)更丰富的可视化，如果数据可以用少量参数来描述。acg不仅显示哪些关联达到统计显著性，还显示关联的大小(统计主效应的置信区间)作为图的背景色的对比色。本文扩展了ACG的可视化，特别针对所有变量都是二进制的情况，通过说明它们的相对频率。这不仅显示了个体的关联程度(用比值比或其他关联指数表示)，也显示了社区层面的关联程度。我们将该方法应用于一个广泛的例子，即出生和童年因素导致情感性精神障碍的发病，使用的数据来自EDSP(早期发育阶段的……

引用次数: 2

Longitudinal Analysis of Adolescents Deviant and Delinquent Behavior: Applications of Latent Class 青少年越轨和犯罪行为的纵向分析:潜在类别的应用

IF 3.1 3区心理学 Q2 PSYCHOLOGY, MATHEMATICAL

Methodology: European Journal of Research Methods for The Behavioral and Social Sciences

Pub Date : 2006-10-16 DOI: 10.1027/1614-2241.2.3.100

Jost Reinecke

This article presents applications of different growth mixture models considering unobserved heterogeneity within the framework of Mplus (Muthen & Muthen, 2001a, 2001b, 2004). Latent class growth mixture models are discussed under special consideration of count variables that can be incorporated into the mixtures via the Poisson and the zero-inflated Poisson model. Fourwave panel data from a German criminological youth study (Boers et al., 2002) is used for the model analyses. Three classes can be obtained from the data: Adolescents with almost no deviant and delinquent activities, a medium proportion of adolescents with a low increase of delinquency, and a small number with a larger growth starting on a higher level. Considering the zero inflation of the data results in better model fits compared to the Poisson model only. Linear growth specifications are almost sufficient. The conditional application of the mixture models includes gender and educational level of the schools as time-independent predictor...

本文介绍了在Mplus框架内考虑未观察到的异质性的不同生长混合模型的应用(Muthen & Muthen, 2001a, 2001b, 2004)。在特别考虑可以通过泊松模型和零膨胀泊松模型纳入混合模型的计数变量的情况下，讨论了潜在类生长混合模型。来自德国犯罪学青年研究(Boers et al.， 2002)的四波面板数据被用于模型分析。从数据中可以得出三个类别:几乎没有越轨和犯罪活动的青少年，中等比例的青少年犯罪增长率低，少数青少年从更高的层次开始增长较大。与泊松模型相比，考虑数据的零膨胀可以得到更好的模型拟合。线性增长规格几乎就足够了。混合模型的条件应用包括学校性别和教育水平作为时间无关的预测因子。

引用次数: 122

Does Money Matter? A Theory-Driven Growth Mixture Model to Explain Travel-Mode Choice with Experimental Data 金钱重要吗?用实验数据解释旅行模式选择的理论驱动的增长混合模型

IF 3.1 3区心理学 Q2 PSYCHOLOGY, MATHEMATICAL

Methodology: European Journal of Research Methods for The Behavioral and Social Sciences

Pub Date : 2006-10-03 DOI: 10.1027/1614-2241.2.3.124

E. Davidov, Kajsa Yang-Hansen, J. Gustafsson, P. Schmidt, S. Bamberg

In the present article we apply a growth mixture model using Mplus via STREAMS to delineate the mechanism underlying travel-mode choice. Three waves of an experimental field study conducted in Frankfurt Main, Germany, are applied for the statistical analysis. Five major questions are addressed: (1) whether the choice of public transport rather than the car changes over time; (2) whether a soft policy intervention to change travel mode choice has any effect on the travel-mode chosen; (3) whether one can identify different groups of people regarding the importance allocated to monetary and time considerations for the decision of which travel mode to use; (4) whether the different subgroups of people have different initial states and rates of change in their travel-model choices; (5) whether sociodemographic variables have an additional effect on the latent class variables and on the changes in travel-mode choice over time. We also found that choice of public transportation in our study is stable over time. ...

在本文中，我们通过STREAMS使用Mplus应用生长混合模型来描述旅行模式选择的机制。在德国法兰克福进行的三波实验实地研究应用于统计分析。研究解决了五个主要问题:(1)选择公共交通工具而不是私家车是否会随着时间的推移而改变;(2)改变出行方式选择的软政策干预是否对出行方式选择产生影响;(3)在决定使用哪种出行方式时，能否区分出不同人群对金钱和时间考虑的重要性;(4)不同亚群的出行模式选择是否具有不同的初始状态和变化率;(5)社会人口变量是否对潜在阶级变量和出行方式选择随时间的变化有额外影响。我们还发现，在我们的研究中，公共交通的选择随着时间的推移是稳定的. ...

引用次数: 12

Mixture of Covariance Structure Models to Identify Different Types of Life Style 混合协方差结构模型识别不同类型的生活方式

IF 3.1 3区心理学 Q2 PSYCHOLOGY, MATHEMATICAL

Methodology: European Journal of Research Methods for The Behavioral and Social Sciences

Pub Date : 2006-10-03 DOI: 10.1027/1614-2241.2.3.86

Petra Stein

A central topic of empirical social research is the problem of unobserved heterogeneity. To solve this problem at least partially, a statistical model is presented: the finite mixture of conditional mean and covariance structure models. In this approach, the expected values in each component of a mixture may depend on normally or nonnormally distributed regressor variables. The expected value and the covariance matrix in each component of the mixture are parameterized using conditional mean and covariance structure models. Three different procedures for estimating the parameters of these models are briefly discussed. The model and the estimation procedures are applied to data of the German General Social Survey 1998 to identify heterogenous types of life style. Since different regression models with latent variables may be used for each type, it is not only possible to cover different types of life style, but also different types of relationships between life style dimensions and the influences of sociode...

实证社会研究的一个中心课题是未观察到的异质性问题。为了解决这一问题，提出了一种统计模型:条件均值和协方差结构模型的有限混合模型。在这种方法中，混合物的每个组成部分的期望值可能取决于正态分布或非正态分布的回归变量。利用条件均值和协方差结构模型参数化了混合模型各组成部分的期望值和协方差矩阵。简要讨论了估计这些模型参数的三种不同方法。将该模型和估计程序应用于1998年德国综合社会调查的数据，以确定生活方式的异质性类型。由于每种类型可以使用不同的带有潜在变量的回归模型，因此不仅可以涵盖不同类型的生活方式，而且还可以涵盖不同类型的生活方式维度与社会影响之间的关系。

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全部化学•材料生命科学医学物理工程技术环境•农林材料科学地球科学法学管理学化学环境科学与生态学计算机科学教育学经济学农林科学人文科学生物学数学物理与天体物理心理学综合性期刊其他工业工程理学历史学农学文学信息工程

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全部 ACS Publications Elsevier ieeexplore Springer The Royal Society of Chemistry Wiley

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Methodology: European Journal of Research Methods for The Behavioral and Social Sciences

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