A structural equation model of conceptual change in physics

A model of conceptual change in physics was tested on introductory‐level, college physics students. Structural equation modeling was used to test hypothesized relationships among variables linked to conceptual change in physics including an approach goal orientation, need for cognition, motivation, and course grade. Conceptual change in physics was determined using gains from pre‐ to post‐administration of the Force Concept Inventory (FCI). Results indicated that need for cognition and approach goals had a significant influence on motivation. Motivation influenced change scores on the FCI both directly, and indirectly, through course grade. Finally, course grade directly influenced conceptual change. The implications of these findings for future research and developing students' conceptual change in physics are discussed. © 2011 Wiley Periodicals, Inc. J Res Sci Teach 48: 901–918, 2011     

Calculating degrees of freedom for a structural equation model

Multivariate Analysis of Categorical Data: Theory. John P. Van de Geer, Newbury Park, CA: Sage, 1993, 104 pages.

Multivariate Analysis of Categorical Data: Applications. John P. Van de Geer, Newbury Park, CA: Sage, 1993, 128 pages.     

Family parameters of achievement: A structural equation model

The aim of the present study was to investigate the effects of several structural and functional characteristics of the family on the child’s actual school achievement. A structural equation model was constructed and its ability to fit the data was tested. It was found that the child’s achievement is directly influenced by the socio-economic status of the family, which is a structural characteristic. The child’s achievement is also directly influenced by the child self-image and by various indications of the family function, such as parental involvement activities and expectations. Furthermore, the results show that the child’s self image is the strongest factor that explains school achievement. Among the many implications that this study offers for educational policy and practice is that children’s achievement may be significantly influenced by altering factors that are outside of school and outside of the students themselves; namely, parental behavior and family functioning.     

On the growth of structural equation modeling in psychological journals

This study investigates the distribution of technical and substantive structural equation modeling articles (SEM) that were published in psychological journals from 1987 to 1994. An inspection of more than 1050 abstracts on PsycLit 1987–1995 (PsycINFO, 1973–1995) revealed a number of clear trends: (a) an increase by year of articles concerned with SEM, (b) an increase in the number of journals that publish structural equation modeling articles, (c) a relatively stable output of technical articles across years, and (d) an increase of substantive articles across years. Furthermore, when the substantive articles are classified as either causal models or confirmatory factor analyses, a similar “growth” trend across years occurs for both categories. We further inspected the growth trend by considering the ratio of SEM articles to the total number of psychology articles and by comparing these results to distributions of analysis of variance, multivariate analysis of variance, regression, and factor analyses articles for the period of 1973 to 1994.     

结构方程模型在科研机构评估中的应用

该文提出利用含有潜变量和显变量的结构方程模型对科研机构进行评估。该方法一方面能揭示潜变量与其显变量之间的关系，另一方面还可分析出各潜变量与综合评价指数之间的联系。该文以重点实验室的评估为例，采用了反映研究成果、承担经费、人才培养、队伍建设和开放交流的5个变量组，利用结构方程模型建立科研机构综合评估指数，对各实验室进行排序。     

Using the friedman method of ranks for model comparison in structural equation modeling

Empirical researchers maximize their contribution to theory development when they compare alternative theory‐inspired models under the same conditions. Yet model comparison tools in structural equation modeling—χ² difference tests, information criterion measures, and screening heuristics—have significant limitations. This article explores the use of the Friedman method of ranks as an inferential procedure for evaluating competing models. This approach has attractive properties, including limited reliance on sample size, limited distributional assumptions, an explicit multiple comparison procedure, and applicability to the comparison of nonnested models. However, this use of the Friedman method raises important issues regarding the lack of independence of observations and the power of the test.     

A structural equation model of the writing process in typically-developing sixth grade children

The purpose of this study was to evaluate how sixth grade children planned, translated, and revised written narrative stories using a task reflecting current instructional and assessment practices. A modified version of the Hayes and Flower (1980) writing process model was used as the theoretical framework for the study. Two hundred one sixth-grade students participated in a three-day writing task. On the first day they generated ideas for their story, on the second day they produced a first draft, and on the third day they revised their draft to produce a final copy. Scores from each day’s writing were used as measured variables representing the latent variables of planning, translating, and revising. Confirmatory structural equation modeling results suggested that the latent variable of planning had a moderate relationship to translating and that translating had a stronger than expected relationship with revising. Significant paths between measured and latent variables demonstrated the relative contribution of skills towards the writing process. The approach used in this study highlighted the linear manner in which intermediate grade children write. Findings suggest that planning had a direct effect on translating, but no direct effect on revising. There was a strong relationship between translating and revising, suggesting few differences between students’ first and final drafts.     

翻译能力结构方程理论模型构建研究

目前国内外学者对PACTE小组提出的翻译能力的构成要素已达成基本共识:翻译能力由双语子能力,语言外子能力,翻译知识子能力,工具子能力,策略子能力和心理生理要素构成。本论文结合结构方程模型构建了翻译能力结构方程理论模型,并分析了各要素之间的相互关系。     

The equal correlation baseline model for comparative fit assessment in structural equation modeling

In this article I describe and evaluate an alternative baseline model for comparative fit assessment of structural equation models and compare it to the standard “null” baseline model. The new “equal correlation” baseline model constrains all variables to have equal, rather than zero, correlations, whereas all variances are free. The new baseline model reflects the reality of atheoretical background correlation in nonex‐perimental data sets, and it improves the ability of comparative fit indices to distinguish between better and worse target models. It also helps to preserve the statistical link between these indices and the noncentral χ² distribution. Also, computing the same comparative fit indices using different baseline models will provide more information about model fit than computing multiple comparative fit indices using the same baseline. I also point out some limitations of the proposed baseline model.     

Confirmation bias in structural equation modeling

In this article, a theoretical and philosophical revision of the concept of fit in structural equation modeling and its relation to a confirmation bias is developed. The neutral character of the fit indexes regarding this issue is argued, yielding the conclusion that the creation of new indexes is not a viable protection against confirmation bias. This protection relies on the model modification strategy and the behavior of scientists, rather than on mathematical or computational statistics. The differentiation between two sets of overidentifying constraints and two dimensions for nested models is introduced, leading to a general model‐modification strategy based on the framework of Popper's view of science.     

Local influence in structural equation models

Local‐influence diagnostics based on maximum likelihood (ML), generalized least squares (GLS), and unweighted least squares (ULS) fit functions are developed for structural equation models (SEMs). The influence of observations, components of observations, and variables is considered. The diagnostics are illustrated with an example data set, and comparisons are made with equivalent global measures of influence. The local influence of the data set on ML and GLS estimates is very similar, but it is much different from that of ULS. The local and global influence of observations is also very different. Although it is not possible to define a uniformly best measure of influence, the local‐influence diagnostics developed here are more versatile than global‐influence diagnostics in assessing an analysis with SEMs.     

Women's path into science and engineering majors: a structural equation model

The intent of this study was to investigate the adequacy of Weidman's (1985 Weidman, J. C. 1985. “Undergraduate socialization: A conceptual approach”. In Higher education: Handbook of theory and research, Edited by: Smart, J. C. Vol. V, 298–322. New York: Agathon Press.  [Google Scholar], 1989 Weidman, J. C. 1989. “The world of higher education: A socialization-theoretical perspective”. In The social world of adolescents: International perspectives, Edited by: Hurrelmann, K. and Engel, U. 87–105. New York: W. de Gruyter.  [Google Scholar]) theoretical undergraduate socialization model as an empirical-based causal model pertaining to women's career path choice into a science or engineering (SE) major via structural equation modeling. Data were obtained from the Beginning Postsecondary Students Longitudinal Study (1996–2001) from the U.S. Department of Education. Results indicate that Weidman's model was somewhat supported. Results from the evaluation of the causal model suggest that women's path into an SE major was influenced by both collegiate and non-collegiate factors, with 1st-year college grades and high school math grades being the dominant indirect influences.     

Errors of inference in structural equation modeling

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.     

基于结构方程模型对医学院校教师心理紧张反应的研究

影响心理紧张反应的因素有年龄、性别、学历、收入等个体特征,对支持利用度、时间控制、环境紧张因素、注意力需求、时间压力、合作需求、工作组织问题以及合作的可能性工作紧张因素,还有负性生活事件紧张因素都是影响教师心理紧张反应的主要因素。年龄越高,工龄越长、心理症状越明显,女性总体幸福感比男性低。工作紧张因素以及社会生活紧张因素都是影响其心理紧张反应的主要因素。     

基于结构方程模型的汽车销售企业客户满意度评价

客户满意度分析是提高汽车销售企业经济效益,提高企业市场竞争力的重要途径。采用结构方程模型,应用偏最小二乘法可以科学的分析客户满意度的调查数据,从而得出提升汽车销售企业客户满意度的具体方法。     

Issues in applied structural equation modeling research

When using the popular structural equation modeling (SEM) methodology, the issues of sample size, method of parameter estimation, assessment of model fit, and capitalization on chance are of great importance in the process of evaluating the results of an empirical study. We focus first on implications of the large‐sample theory underlying applications of the methodology. The utility for applied contexts of the asymptotically distribution‐free parameter estimation and model testing method is discussed next. We then argue for wider use of a recently developed, non conventional model‐fit assessment strategy in SEM. We conclude by discussing the issue of capitalization on chance, primarily in situations in which exploratory and confirmatory analyses are conducted on the same data set.     

The relation between classroom management and mathematics achievement: A multilevel structural equation model

The impact of teachers on their students’ academic achievement continues to be an area of inquiry. One area not fully explored is the relation between teachers’ behavior and classroom management (CM) skills, student motivation, and student achievement. We examined these relations using a multi‐level structural equation model. Data included Behavior Management subscale scores of the Classroom Assessment Scoring System for 247 fourth and fifth grade teachers, indicators of academic motivation, and end‐of‐year state standardized mathematics assessment results for 4,847 students from the National Center of Teacher Effectiveness Main Study. The results indicate teachers’ CM skills have a significant direct effect on student motivation and a significant indirect effect on students’ math achievement, suggesting that students in classrooms of teachers with better CM are more motivated to learn math and have higher math achievement scores. This underscores the importance of helping teachers increase their use of evidence‐based classroom management techniques.