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1.
Behavior genetic modeling is a prominent application of multi-group structural equation modeling (SEM). It decomposes phenotypic variance into genetic and environmental sources by leveraging the covariation within and between kin pairs. Although any SEM program with multi-group capabilities can be employed, the software program, Mx, has dominated behavior genetics research. Indeed, even though Mx has not been maintained since 2011, it remains the most popular SEM program in Behavior Genetics articles published in 2016 and 2017. Given the persistence of Mx, the aim of this article is to understand Mx’s performance relative to other popular behavior genetic programs. Through this process, programs employed in behavior genetics research are identified, and their relevant technical features and accessibility are compared. Finally, the relative strengths and limitations of the programs are discussed, and recommendations are provided for behavior genetics researchers.  相似文献   

2.
School psychologists in the United States are not nearly as diverse demographically as the students they serve (T.K. Fagan & P.S. Wise, 2000). A.H. Miranda and P.B. Gutter (2002) investigated the number of diversity‐related articles in four leading school psychology journals from 1990 to 1999 and found that there was an increase in the percentage of articles in these journals that were diversity related as compared to a study done by R.M. Wiese Rogers (1992) that examined school psychology journals from 1975 to 1990. There was a particular increase in diversity‐related articles appearing from 1995 to 1999. The present study examined school psychology journals from 2000 to 2003 to determine whether this increase was an aberration or an indication of a longer term change. Results indicate a continued trend toward more diversity‐related articles in the school psychology literature, but several gaps remain. Implications for the field are discussed. © 2007 Wiley Periodicals, Inc.  相似文献   

3.
Although methodology articles have increasingly emphasized the need to analyze data from two members of a dyad simultaneously, the most popular method in substantive applications is to examine dyad members separately. This might be due to the underappreciation of the extra information simultaneous modeling strategies can provide. Therefore, the goal of this study was to compare multiple growth curve modeling approaches for longitudinal dyadic data (LDD) in both structural equation modeling and multilevel modeling frameworks. Models separately assessing change over time for distinguishable dyad members are compared to simultaneous models fitted to LDD from both dyad members. Furthermore, we compared the simultaneous default versus dependent approaches (whether dyad pairs’ Level 1 [or unique] residuals are allowed to covary and differ in variance). Results indicated that estimates of variance and covariance components led to conflicting results. We recommend the simultaneous dependent approach for inferring differences in change over time within a dyad.  相似文献   

4.
How is affective change rated with positive adjectives such as good related to change rated with negative adjectives such as bad? Two nested perfect and imperfect forms of dynamic bipolarity are defined using latent change structural equation models based on tetrads of items. Perfect bipolarity means that latent change scores correlate -1. Meaningful structural equation modeling (SEM) analyses of self-rated affect may require analyzing polychoric correlations, if self-ratings are collected using ordered categories. The models were applied to 6 4-wave datasets from Steyer and Riedl (2004). Results suggest that perfect bipolarity is generally compatible with valence self-ratings, whereas imperfect bipolarity is compatible with tension and energy self-ratings. Methodological and substantive limits of the approach are discussed.  相似文献   

5.
This article discusses replication sampling variance estimation techniques that are often applied in analyses using data from complex sampling designs: jackknife repeated replication, balanced repeated replication, and bootstrapping. These techniques are used with traditional analyses such as regression, but are currently not used with structural equation modeling (SEM) analyses. This article provides an extension of these methods to SEM analyses, including a proposed adjustment to the likelihood ratio test, and presents the results from a simulation study suggesting replication estimates are robust. Finally, a demonstration of the application of these methods using data from the Early Childhood Longitudinal Study is included. Secondary analysts can undertake these more robust methods of sampling variance estimation if they have access to certain SEM software packages and data management packages such as SAS, as shown in the article.  相似文献   

6.
From the time of William James, psychologists have posited individually importance-weighted-average models (IWAMs) in which weighting specific attributes by individual measures of importance improves prediction of the global outcome measures. Because IWAMs cause much confusion, we briefly review a general taxonomic paradigm and structural equation models for testing IWAMs, and demonstrate its application for 2 simulated and 3 diverse “real” data applications (multidimensional measures of self-concept, quality of life, and job satisfaction). Consistent across the real data applications and previous research more generally, there is surprisingly little support for IWAMs when tested appropriately. In these diverse tests of IWAMs we integrate new approaches such as exploratory structural equation modeling (SEM), alternative approaches to constructing latent interactions, application of bifactor models, modeling method and item-wording effects, and the juxtaposition of model evaluation in relation to goodness of fit (typically used in SEM studies) and variance explained (typically used in multiple regression tests of IWAMs).  相似文献   

7.
It is often of interest to estimate partial or semipartial correlation coefficients as indexes of the linear association between 2 variables after partialing one or both for the influence of covariates. Squaring these coefficients expresses the proportion of variance in 1 variable explained by the other variable after controlling for covariates. Methods exist for testing hypotheses about the equality of these coefficients across 2 or more groups, but they are difficult to conduct by hand, prone to error, and limited to simple cases. A unified framework is provided for estimating bivariate, partial, and semipartial correlation coefficients using structural equation modeling (SEM). Within the SEM framework, it is straightforward to test hypotheses of the equality of various correlation coefficients with any number of covariates across multiple groups. LISREL syntax is provided, along with 4 examples.  相似文献   

8.
Over the past decade and a half, methodologists working with structural equation modeling (SEM) have developed approaches for accommodating multilevel data. These approaches are particularly helpful when modeling data that come from complex sampling designs. However, most data sets that are associated with complex sampling designs also include observation weights, and methods to incorporate these sampling weights into multilevel SEM analyses have not been addressed. This article investigates the use of different weighting techniques and finds, through a simulation study, that the use of an effective sample size weight provides unbiased estimates of key parameters and their sampling variances. Also, a popular normalization technique of scaling weights to reflect the actual sample size is shown to produce negatively biased sampling variance estimates, as well as negatively biased within-group variance parameter estimates in the small group size case.  相似文献   

9.
Meta-analytic structural equation modeling (MA-SEM) is increasingly being used to assess model-fit for variables' interrelations synthesized across studies. MA-SEM researchers have analyzed synthesized correlation matrices using structural equation modeling (SEM) estimation that is designed for covariance matrices. This can produce incorrect model-fit chi-square statistics, standard error estimates (Cudeck, 1989), or both for parameters that are not scale free or that describe a scale-noninvariant model unless corrected SEM estimation is used to analyze the correlations. This study introduced univariate and multivariate approximate methods for synthesizing covariance matrices for use in MA-SEM. A simulation study assessed the approximate methods by estimating parameters in a scale-noninvariant model using synthesized covariances versus synthesized correlations with and without the appropriate corrections. Standard error bias was noted only for uncorrected analyses of pooled correlations. Chi-square model-fit statistics were overly conservative except when covariance matrices were analyzed. Benefits and limitations of this approximate method are presented and discussed.  相似文献   

10.
In 21 years, CES has appeared 87 times, has had 7 editors, and has had 85 pople serving on the editorial board. A total of 1, 103 articles on various topics has appeared, including 983 substantive articles, authored by 997 people alone or as multiple authors. Topical changes are analyzed and discussed, along with changes in authorship and some related trends. Comparisons are made with other journals for which similar analyses have been done.  相似文献   

11.
教育期刊论文的情况往往是教育研究情况的一种反映.中外主要高等教育期刊刊名分别为<中国高等教育>(China Higher Education)、<高等教育研究>(中国)(Journal of Higher E-ducation)、Higher Education、Research of Higher Education.本文基于这四种高等教育期刊的相关参数分别建立相应的高等教育合作网,从论文作者数目及不同论文作者间的合作关系的角度,揭示中国与国际高等教育研究的特点和差异,并为它们的进一步发展提供启发性和指导性建议.  相似文献   

12.
Partial least squares structural equation modeling (PLS-SEM) has become a key multivariate statistical modeling technique that educational researchers frequently use. This paper reviews the uses of PLS-SEM in 16 major e-learning journals, and provides guidelines for improving the use of PLS-SEM as well as recommendations for future applications in e-learning research. A total of 53 articles using PLS-SEM published in January 2009–August 2019 are reviewed. We assess these published applications in terms of the following key criteria: reasons for using PLS-SEM, model characteristics, sample characteristics, model evaluations and reporting. Our results reveal that small sample size and nonnormal data are the first two major reasons for using PLS-SEM. Moreover, we have identified how to extend the applications of PLS-SEM in the e-learning research field.  相似文献   

13.
Minor cross-loadings on non-targeted factors are often found in psychological or other instruments. Forcing them to zero in confirmatory factor analyses (CFA) leads to biased estimates and distorted structures. Alternatively, exploratory structural equation modeling (ESEM) and Bayesian structural equation modeling (BSEM) have been proposed. In this research, we compared the performance of the traditional independent-clusters-confirmatory-factor-analysis (ICM-CFA), the nonstandard CFA, ESEM with the Geomin- or Target-rotations, and BSEMs with different cross-loading priors (correct; small- or large-variance priors with zero mean) using simulated data with cross-loadings. Four factors were considered: the number of factors, the size of factor correlations, the cross-loading mean, and the loading variance. Results indicated that ICM-CFA performed the worst. ESEMs were generally superior to CFAs but inferior to BSEM with correct priors that provided the precise estimation. BSEM with large- or small-variance priors performed similarly while the prior mean for cross-loadings was more important than the prior variance.  相似文献   

14.
Although structural equation modeling (SEM) is one of the most comprehensive and flexible approaches to data analysis currently available, it is nonetheless prone to researcher misuse and misconceptions. This article offers a brief overview of the unique capabilities of SEM and discusses common sources of user error in drawing conclusions from these analyses. We make recommendations to guide proper analytical practices and appropriate inferences and provide references for more advanced study. © 2007 Wiley Periodicals, Inc. Psychol Schs 44: 461–470, 2007.  相似文献   

15.
Theoretical and technical research in structural equation modeling (SEM) focuses on the procedures per se rather than on substantive applications of the procedures. An earlier bibliography annotated nearly 300 technical publications about latent variable models. Since that bibliography was published in 1991, there has been a distinct surge in theoretical‐technical publications, organized around model evaluation, multifaceted extensions to levels, groups, and occasions, ordinal level data, statistical power, categorical data, and new computer programs (Mx, MECOSA, RAMONA, SEPath). This article updates the earlier bibliography to acknowledge the growth of more specialized refinements of SEM and to guide developers, researchers, and instructors. As an indicator of the surge in this literature, over 320 new publications are annotated in this version within a 9‐part categorization system. The groupings were selected to be reasonably exhaustive and not too extensive, resulting in this set: (a) Model Specification and Identification, (b) Model Estimation (including asymptotics), (c) Model Testing, Evaluation, and Modification, d) Monte Carlo/Simulation, (e) Reviews and Critiques/Debates, (0 Introductory and Pedagogical, (g) Philosophical, (h) Special Purpose Models (e.g., multitrait‐multimethod, multilevel, behavior genetics, developmental/change), and (i) Computer Programs and Programming.  相似文献   

16.
One common application of structural equation modeling (SEM) involves expressing and empirically investigating causal explanations. Nonetheless, several aspects of causal explanation that have an impact on behavioral science methodology remain poorly understood. It remains unclear whether applications of SEM should attempt to provide complete explanations or partial explanations. Moreover, it remains unclear what sorts of things researchers can best take as causes and effects. Finally, the meaning of causal assertions itself remains poorly understood. Attempting to clarify the use of structural equations as causal explanations by addressing these issues has implications for behavioral science methodology because applications of SEM typically remain vague about causation and thus about their substantive conclusions. Research aimed at clarifying these issues can lead to a sharper and more refined use of SEM for causal explanation, and by extension, clarify behavioral science methodology more generally.  相似文献   

17.
Bayesian approaches to modeling are receiving an increasing amount of attention in the areas of model construction and estimation in factor analysis, structural equation modeling (SEM), and related latent variable models. However, model diagnostics and model criticism remain relatively understudied aspects of Bayesian SEM. This article describes and illustrates key features of Bayesian approaches to model diagnostics and assessing data–model fit of structural equation models, discussing their merits relative to traditional procedures.  相似文献   

18.
Both structural equation modeling (SEM) and item response theory (IRT) can be used for factor analysis of dichotomous item responses. In this case, the measurement models of both approaches are formally equivalent. They were refined within and across different disciplines, and make complementary contributions to central measurement problems encountered in almost all empirical social science research fields. In this article (a) fundamental formal similiarities between IRT and SEM models are pointed out. It will be demonstrated how both types of models can be used in combination to analyze (b) the dimensional structure and (c) the measurement invariance of survey item responses. All analyses are conducted with Mplus, which allows an integrated application of both approaches in a unified, general latent variable modeling framework. The aim is to promote a diffusion of useful measurement techniques and skills from different disciplines into empirical social research.  相似文献   

19.
Recently, concern has been voiced within the academy regarding the marginalization of legal scholarship within the criminology and criminal justice (CCJ) discipline. Although conventional wisdom and anecdotal evidence indicate that it is difficult to get legal scholarship published in CCJ journals, there is a dearth of empirical evidence on the representation of legal scholarship in CCJ journals. The present study assesses the representation of legal scholarship in 20 CCJ journals from 2005 to 2015, examining both trends over time and variation across journals. Findings indicate legal scholarship comprises a very small portion of articles published, there has been a steep decline in the number of legal articles published in recent years, and the average number of legal articles per year is very low for nearly all of the journals in the sample. The implications of the marginalization of legal scholarship within the CCJ discipline are discussed.  相似文献   

20.

The APA Task Force on Statistical Inference recently recommended reporting effect sizes alongside results of statistical significance tests. The purpose of this article is to investigate effect size usage in gifted education research and to follow up on a similar investigation published by Plucker (1997). A content analysis of effect size reporting was conducted of articles published in the Journal for the Education of the Gifted, Roeper Review, and Gifted Child Quarterly from 1995–2000. Results of the present study were similar to the findings of Plucker (1997): No statistical difference in reporting was found across journals or across years, and a moderate difference was found between effect size reporting in univariate versus multivariate statistics. The benefits to gifted education research of understanding the relationship among sample size, effect size, and statistical power are discussed.  相似文献   

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