共查询到20条相似文献，搜索用时 31 毫秒
1.
Wai Chan 《Structural equation modeling》2013,20(2):326-346
In social science research, an indirect effect occurs when the influence of an antecedent variable on the effect variable is mediated by an intervening variable. To compare indirect effects within a sample or across different samples, structural equation modeling (SEM) can be used if the computer program supports model fitting with nonlinear constraints. However, such an option is not routinely available in every popular software program. In this study, the basic idea of generating covariance-equivalent models in SEM is given and a sequential model fitting method is proposed as an alternative without the need to use nonlinear constraints. Under this method, the hypothesized model is transformed into a set of successive covariance-equivalent models so that an indirect effect is reparameterized as a single model parameter in the final transformed model. Real examples are given to illustrate how the proposed method is implemented using EQS, a SEM program that currently does not support the analysis with nonlinear constraints. 相似文献
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Rens van de Schoot Herbert Hoijtink Michael N. Hallquist Paul A. Boelen 《Structural equation modeling》2013,20(4):593-609
Researchers in the behavioral and social sciences often have expectations that can be expressed in the form of inequality constraints among the parameters of a structural equation model resulting in an informative hypothesis. The questions they would like an answer to are “Is the hypothesis Correct” or “Is the hypothesis incorrect?” We demonstrate a Bayesian approach to compare an inequality-constrained hypothesis with its complement in an SEM framework. The method is introduced and its utility is illustrated by means of an example. Furthermore, the influence of the specification of the prior distribution is examined. Finally, it is shown how the approach proposed can be implemented using Mplus. 相似文献
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A multiple testing procedure for examining the assumption of normality that is often made in analyses of incomplete data sets is outlined. The method is concerned with testing normality within each missingness pattern and arriving at an overall statement about normality using the available data. The approach is readily applied in empirical research with missing data using the popular software Mplus, Stata, and R. The procedure can be used to ascertain a main assumption underlying frequent applications of maximum likelihood in incomplete data modeling with continuous outcomes. The discussed approach is illustrated with numerical examples. 相似文献
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S. Mason Garrison 《Structural equation modeling》2018,25(6):972-977
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
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Michael F. Bosco 《Computer Science Education》2013,23(2):117-130
Teaching software engineering (SE) is a difficult but critical task, whether students are undergraduates, graduates, or professionals. Most designs of undergraduate courses are based on a large project. During this project, students apply methods that have been introduced during lectures. Project schedules usually follow life cycles corresponding to the steps that lead to the creation of new pieces of software. My intention is to analyze the difficulties that occur in SE undergraduate courses and to propose a method to improve course quality and to meet with industrial needs that are more reusability‐ and maintenance‐oriented. This article outlines a typical course and some of its weaknesses. Then, it proposes changes and discusses a different way of teaching SE based on the following ideas:
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Apply a reverse engineering life cycle that starts by making students deal with code, and, step by step, parts of design, specification, and requirement documents. This phase aims to motivate students, to make them critical of existing software, and to teach them norms, methods, and standards.
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Make students follow the usual feedback‐directed life cycle to complete the software they have analyzed during the first phase.
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Structural equation modeling (SEM) techniques were used to compare 5 methods of assessing HIV/AIDS sexual risk in a large prediction model. These were: (a) multiple measures; (b) a single latent factor; (c) modifying the computation of the dependent variables used in Methods 1 and 2 to weight sexual encounters by specific partner risk; (d) use of risk composites, obtained by multiplying number of sexual partners by number of occasions of unprotected sex; and (e) use of risk indexes that assign a number based on responses to general questions about risk behaviors. Data from 452 at‐risk women from a New England community were analyzed in 5 versions of an HIV/AIDS sexual risk prediction model. Models were compared in terms of SEM empirical fit indexes (x2 [df], average absolute standardized residuals, and Comparative Fit Index); significant paths, explained variance, theoretical fit, and simplicity. Results indicate that: (a) multiple measures and latent factor models are preferable to all others by each of the standards of comparison, (b) in the composite dependent variable models, including information about the partners' number of partners provided little additional explained variance beyond knowing the number of occasions of unprotected sex, and (c) dependent measures that did not remain close to Centers for Disease Control criteria may not be adequately predicting HIV/AIDS sexual risk. Several recommendations are presented for selecting an appropriate conceptualization of HIV/AIDS sexual risk. 相似文献
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Despite its importance to structural equation modeling, model evaluation remains underdeveloped in the Bayesian SEM framework. Posterior predictive p-values (PPP) and deviance information criteria (DIC) are now available in popular software for Bayesian model evaluation, but they remain underutilized. This is largely due to the lack of recommendations for their use. To address this problem, PPP and DIC were evaluated in a series of Monte Carlo simulation studies. The results show that both PPP and DIC are influenced by severity of model misspecification, sample size, model size, and choice of prior. The cutoffs PPP < 0.10 and ?DIC > 7 work best in the conditions and models tested here to maintain low false detection rates and misspecified model selection rates, respectively. The recommendations provided in this study will help researchers evaluate their models in a Bayesian SEM analysis and set the stage for future development and evaluation of Bayesian SEM fit indices. 相似文献
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Latent class analysis (LCA) is an increasingly popular tool that researchers can use to identify latent groups in the population underlying a sample of responses to categorical observed variables. LCA is most commonly used in an exploratory fashion whereby no parameters are specified a priori. Although this exploratory approach is reasonable when very little prior research has been conducted in the area under study, it can be very limiting when much is already known about the variables and population. Confirmatory latent class analysis (CLCA) provides researchers with a tool for modeling and testing specific hypotheses about response patterns in the observed variables. CLCA is based on placing specific constraints on the parameters to reflect these hypotheses. The popular and easy-to-use latent variable modeling software package Mplus can be used to conduct a variety of CLCA types using these parameter constraints. This article focuses on the basic principles underlying the use of CLCA, and the Mplus programming code necessary for carrying it out. 相似文献
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Lifang Deng 《Structural equation modeling》2013,20(4):552-567
Multigroup structural equation modeling (SEM) plays a key role in studying measurement invariance and in group comparison. However, existing methods for multigroup SEM assume that different samples are independent. This article develops a method for multigroup SEM with correlated samples. Parallel to that for independent samples, the focus here is on the cross-group stability of the within-group structure and parameters. In particular, the method does not require the specification of any between-group relationship. Rescaled and adjusted statistics as well as sandwich-type covariance matrices make the developed method work for possibly nonnormal variables with finite 4th-order moments. The method is applied to a longitudinal data set on the development of entrepreneurial teams across 4 phases. Detailed analysis is provided regarding the stability of the effect of psychological compatibility on team performance, as it is mediated by fairness perception and team cohesion. 相似文献
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《The Journal of educational research》2012,105(5):275-282
Abstract In education research, statistical significance and effect size are 2 sides of 1 coin; they complement each other but they do not substitute for each other. Good research practice requires that, to make sound research decisions, both sides should be considered. In a simulation study, the sampling variability of 2 popular effect-size measures (d and R 2) was examined. The variability showed that what is statistically significant may not be practically meaningful, and what appears to be practically meaningful could have been the result of sampling error, thus not trustworthy. Some practical guidelines are suggested for combining the 2 sources of information in research practice. 相似文献
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Investigating the fit of a parametric model plays a vital role in validating an item response theory (IRT) model. An area that has received little attention is the assessment of multiple IRT models used in a mixed-format test. The present study extends the nonparametric approach, proposed by Douglas and Cohen (2001), to assess model fit of three IRT models (three- and two-parameter logistic model, and generalized partial credit model) used in a mixed-format test. The statistical properties of the proposed fit statistic were examined and compared to S-X2 and PARSCALE’s G2. Overall, RISE (Root Integrated Square Error) outperformed the other two fit statistics under the studied conditions in that the Type I error rate was not inflated and the power was acceptable. A further advantage of the nonparametric approach is that it provides a convenient graphical inspection of the misfit. 相似文献
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Ghulam Qasim Mehboob ur Rehman A. Kareem . School of Communication Information Engineering Shanghai University Shanghai China . Gomal University D.I.Kham Pakistan 《上海大学学报(英文版)》2000,4(1):27-30
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In the presence of omitted variables or similar validity threats, regression estimates are biased. Unbiased estimates (the causal effects) can be obtained in large samples by fitting instead the Instrumental Variables Regression (IVR) model. The IVR model can be estimated using structural equation modeling (SEM) software or using Econometric estimators such as two-stage least squares (2SLS). We describe 2SLS using SEM terminology, and report a simulation study in which we generated data according to a regression model in the presence of omitted variables and fitted (a) a regression model using ordinary least squares, (b) an IVR model using maximum likelihood (ML) as implemented in SEM software, and (c) an IVR model using 2SLS. Coverage rates of the causal effect using regression methods are always unacceptably low (often 0). When using the IVR model, accurate coverage is obtained across all conditions when N = 500. Even when the IVR model is misspecified, better coverage than regression is generally obtained. Differences between 2SLS and ML are small and favor 2SLS in small samples (N ≤ 100). 相似文献
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《Structural equation modeling》2013,20(2):217-243
Ipsative data (individual scores subject to a constant-sum constraint), suggested to minimize response bias, are sometimes observed in behavioral sciences. Chan and Bentler (1993, 1996) proposed a method to analyze ipsative data in a single-group case. Cheung and Chan (2002) extended the method to multiple-group analysis. However, these methods require tedious procedures on formulating within- and between-group constraints and recovering the parameter estimates and their standard errors. A direct estimation method, which is equivalent to Chan and Bentler's method with an alternative model specification, is proposed in this article. The 1st-order factor-analytic ipsative model in Chan and Bentler's method is reparameterized as a restricted 2nd-order factor-analytic model with fixed factor loading matrix reflecting the ipsative properties in the direct estimation method. The direct estimation method can be easily extended to test measurement invariance properties in multiple-group analysis. Issues related to ipsative models are also addressed. 相似文献
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《Structural equation modeling》2013,20(3):347-368
Several papers have been devoted to the use of structural equation modeling (SEM) software in fitting autoregressive moving average (ARMA) models to a univariate series observed in a single subject. Van Buuren (1997) went beyond specification and examined the nature of the estimates obtained with SEM software. Although the results were mixed, he concluded that these parameter estimates resemble true maximum likelihood (ML) estimates. Molenaar (1999) argued that the negative findings for pure moving average models might be due to the absence of invertibility constraints in Van Buuren's simulation experiment. The aim of this article is to (a) reexamine the nature of SEM estimates of ARMA parameters; (b) replicate Van Buuren's simulation experiment in light of Molenaar's comment; and (c) examine the behavior of the log-likelihood ratio test. We conclude that estimates of ARMA parameters obtained with SEM software are identical to those obtained by univariate stochastic model preliminary estimation, and are not true ML estimates. Still, these estimates, which may be viewed as moment estimates, have the same asymptotic properties as ML estimates for pure autoregressive (AR) processes. For pure moving average (MA) processes, they are biased and less efficient. The estimates from SEM software for mixed processes seem to have the same asymptotic properties as ML estimates. Furthermore, the log-likelihood ratio is reliable for pure AR processes, but this is not the case for pure MA processes. For mixed processes, the behavior of the log-likelihood ratio varies, and in this case these statistics should be handled with caution. 相似文献
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鲁晓丽 《漯河职业技术学院学报》2008,7(2):135-136
随着计算机辅助设计软件的不断发展与普及,以及一些先进设备的引进,对制图教学提出了更高、更广泛的要求。这就要求我们要打破传统的教学模式,建立起与生产技术的发相适应的教学模式。本文通过阐述传统机械制图教学的缺点及三维实体设计的优越性,提出了三维“实体化教学”。与传统机械制图教学相比,体现了课程的实用性与科学性。 相似文献
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Reena Cheruvalath 《Educational Research and Evaluation》2013,19(3):283-297
This study has been conducted to show that there is a recent trend in engineering colleges in India that students who are considered to be highly intelligent show poor academic performance during their 1st year. This article is proposed to examine the role of motivation factors such as teaching methods and learning material in the academic performance of engineering and technological students in India. A test was carried out among engineering students. A total of 200 male and female students participated in this test. A 2-group discriminator analysis was done to analyse the data. The results showed that there was a significant correlation (p = 0.000) between motivation factors and academic performance of engineering students. The higher the rating of these factors by the students, the higher their performance. 相似文献
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介绍了形式化方法和形式化规格说明语言Z语言，利用Z语言对软件需求进行了严格定义，在严格的数学基础上进行软件开发，以获得更好的软件性能．利用形式化方法的需求分析，有助于发现需求中隐含的不一致性、二义性和不完整性，对其进行更深入精确的理解，从而进行规范化管理． 相似文献