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1.
This study examines how a political entertainment film (Man of the Year) can impact an individual's political discussion intent after the same political topic is made salient in a subsequent news story. In addition, a process of communication influence is assessed when the roles of negative emotion and narrative engagement are considered as potential mediators of the relationship between political entertainment film viewing and political discussion intent. Seven hypotheses serve as the foundation for this experimental study, and structural equation modeling was used to test these hypotheses. Results reveal there was no direct influence of political entertainment film viewing on political discussion intent, but there was an indirect effect through negative emotion. Furthermore, narrative engagement emerged as a predictor of political discussion intent and a mediator of the association between negative emotion and political discussion intent.  相似文献   

2.
The current widespread availability of software packages with estimation features for testing structural equation models with binary indicators makes it possible to investigate many hypotheses about differences in proportions over time that are typically only tested with conventional categorical data analyses for matched pairs or repeated measures, such as McNemar’s chi-square. The connection between these conventional tests and simple longitudinal structural equation models is described. The equivalence of several conventional analyses and structural equation models reveals some foundational concepts underlying common longitudinal modeling strategies and brings to light a number of possible modeling extensions that will allow investigators to pursue more complex research questions involving multiple repeated proportion contrasts, mixed between-subjects × within-subjects interactions, and comparisons of estimated membership proportions using latent class factors with multiple indicators. Several models are illustrated, and the implications for using structural equation models for comparing binary repeated measures or matched pairs are discussed.  相似文献   

3.
Structural equation models have wide applications. One of the most important issues in analyzing structural equation models is model comparison. This article proposes a Bayesian model comparison statistic, namely the L ν-measure for both semiparametric and parametric structural equation models. For illustration purposes, we consider a Bayesian semiparametric approach for estimation and model comparison in the context of structural equation models with fixed covariates. A finite dimensional Dirichlet process is used to model the crucial latent variables, and a blocked Gibbs sampler is implemented for estimation. Empirical performance of the L ν-measure is evaluated through a simulation study. Results obtained indicate that the L ν-measure, which additionally requires very minor computational effort, gives satisfactory performance. Moreover, the methodologies are demonstrated through an example with a real data set on kidney disease. Finally, the application of the L ν-measure to Bayesian semiparametric nonlinear structural equation models is outlined.  相似文献   

4.
Abstract

Biggs' Presage–Process–Product (3P) model provides a flexible model for testing hypotheses about intra-psychic and contextual effects on student learning processes and outcomes; however, few empirical studies have effectively tested the longitudinal and reciprocal effects implied by the model. The current study provides an empirical test of theorised reciprocal relationships operating over time implied by the 3P model between perceived teaching quality and approaches to learning. The current study examines a longitudinal sample of Japanese university students (n = 1348; female = 404) from 18 degree programmes. Data from a reciprocal latent model were analysed using structural equation modelling. Modelling identified significant reciprocal effects between teaching quality and deep approaches to learning. Deep (positively) and surface (negatively) predicted annualised GPA (moderate and large effects, respectively). Consistent with a systems theory perspective on teaching and learning, longitudinal results supported hypothesised reciprocal relationships between perceptions of teaching quality and approaches. Implications for theory and practice are discussed.  相似文献   

5.
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6.
Identification of structural equation models remains a challenge to many researchers. Although empirical tests of identification are readily available in structural equation modeling software, these examine local identification and rely on sample estimates of parameters. Rules of identification are available, but do not include all models encountered in practice. In this article we provide 2 rules of identification: the 2+ emitted paths rule and the exogenous X rule. The former is a necessary condition of identification and the latter is a sufficient condition. We explain and prove each of these rules and provide illustrations of their application. These rules extend the coverage of structural equation models that we can check for identification. We also explain how they can be part of a piecewise identification strategy that extends their use even further.  相似文献   

7.
A didactic collection of multivariate covariance and mean structure hypotheses is presented, which can be tested using structural equation modeling. The hypotheses reflect specific structures of the manifest covariance matrix or means, which are often of interest in social, behavioral, or educational research or represent assumptions of widely applied multivariate analysis methods. This large-sample method (a) is generally applicable with normal and nonnormal data (particularly with very large samples in the latter case), (b) can be considered complementing corresponding likelihood ratio tests in the nonnormality case with very large samples, and (c) is straightforwardly implemented in widely circulated structural modeling programs such as LISREL, EQS, AMOS, RAMONA, and SEPATH. The approach is illustrated using data from a two-group cognitive intervention study.  相似文献   

8.
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9.
MplusAutomation is a package for R that facilitates complex latent variable analyses in Mplus involving comparisons among many models and parameters. More specifically, MplusAutomation provides tools to accomplish 3 objectives: to create and manage Mplus syntax for groups of related models; to automate the estimation of many models; and to extract, aggregate, and compare fit statistics, parameter estimates, and ancillary model outputs. We provide an introduction to the package using applied examples including a large-scale simulation study. By reducing the effort required for large-scale studies, a broad goal of MplusAutomation is to support methodological developments in structural equation modeling using Mplus.  相似文献   

10.
In this article we describe a structural equation modeling (SEM) framework that allows nonnormal skewed distributions for the continuous observed and latent variables. This framework is based on the multivariate restricted skew t distribution. We demonstrate the advantages of skewed SEM over standard SEM modeling and challenge the notion that structural equation models should be based only on sample means and covariances. The skewed continuous distributions are also very useful in finite mixture modeling as they prevent the formation of spurious classes formed purely to compensate for deviations in the distributions from the standard bell curve distribution. This framework is implemented in Mplus Version 7.2.  相似文献   

11.
In order to examine the relationship between broad personality traits and learning approaches, 852 university students completed the NEO-FFI [Costa, P. T., Jr., & McCrae, R. R. (1992). Revised NEO Personality Inventory (NEO-PI-R) and NEO Five-Factor Inventory (NEO-FFI): Professional manual. Odessa, FL: Psychological Assessment Resources] and SPQ [Biggs, J. B. (1987). The Study Process Questionnaire manual. Victoria: Australian Council for Educational Research], which assess personality and learning approaches, respectively. Seven previous studies were used to generate hypotheses on the relationship between these two measures, but only the positive link between Openness to Experience and Deep learning was supported by both correlational and structural equation modelling tests. Openness was also found to be negatively linked to Surface learning, but other Big Five traits were not saliently associated with learning approaches. Results indicate that the overlap between learning approaches and personality traits is lower than previously suggested. Implications are discussed.  相似文献   

12.
Several studies have focused on the role of students’ conceptions of intellectual ability, the learning process and the self-efficacy. However, these three parameters have not been integrated and analysed within the same model. Against this background, the objective of our research is to identify the links that develop between these three constructs. To this end, we have put forward two hypotheses: 1. The conception that intelligence is constructed directly and positively affects the conception that learning is a constructive process. This has a positive impact on perceived self-efficacy. 2. The conception that intelligence is a fixed trait directly and positively affects the conception that learning is a reproductive process and leads to lower perceptions of self-efficacy. To test these hypotheses, we conducted research using a questionnaire distributed among 1112 students in their last year of primary school. The questionnaires were subject to statistical analysis using structural equation modelling. The results confirm our hypotheses and thus show the relevance of our model.  相似文献   

13.
Mixed-dyadic data, collected from distinguishable (nonexchangeable) or indistinguishable (exchangeable) dyads, require statistical analysis techniques that model the variation within dyads and between dyads appropriately. The purpose of this article is to provide a tutorial for performing structural equation modeling analyses of cross-sectional and longitudinal models for mixed independent variable dyadic data, and to clarify questions regarding various dyadic data analysis specifications that have not been addressed elsewhere. Artificially generated data similar to the Newlywed Project and the Swedish Adoption Twin Study on Aging were used to illustrate analysis models for distinguishable and indistinguishable dyads, respectively. Due to their widespread use among applied researchers, the AMOS and Mplus statistical analysis software packages were used to analyze the dyadic data structural equation models illustrated here. These analysis models are presented in sufficient detail to allow researchers to perform these analyses using their preferred statistical analysis software package.  相似文献   

14.
Dynamic structural equation modeling (DSEM) is a novel, intensive longitudinal data (ILD) analysis framework. DSEM models intraindividual changes over time on Level 1 and allows the parameters of these processes to vary across individuals on Level 2 using random effects. DSEM merges time series, structural equation, multilevel, and time-varying effects models. Despite the well-known properties of these analysis areas by themselves, it is unclear how their sample size requirements and recommendations transfer to the DSEM framework. This article presents the results of a simulation study that examines the estimation quality of univariate 2-level autoregressive models of order 1, AR(1), using Bayesian analysis in Mplus Version 8. Three features are varied in the simulations: complexity of the model, number of subjects, and number of time points per subject. Samples with many subjects and few time points are shown to perform substantially better than samples with few subjects and many time points.  相似文献   

15.
Abstract

This study investigated cultural variations between two samples of Arab and American distance learners (N = 190). The overarching purpose was to chart the underlying relationships between learner self-regulation and cultural orientation within distance education environments using structural equation modeling. The study found significant differences between Arab and American students on all but one variable. In the best-fitting model, only future orientation, a cultural variable, explained variances in learner self-regulation.  相似文献   

16.
Multivariate meta-analysis has become increasingly popular in the educational, social, and medical sciences. It is because the outcome measures in a meta-analysis can involve more than one effect size. This article proposes 2 mathematically equivalent models to implement multivariate meta-analysis in structural equation modeling (SEM). Specifically, this article shows how multivariate fixed-, random- and mixed-effects meta-analyses can be formulated as structural equation models. metaSEM (a free R package based on OpenMx) and Mplus are used to implement the proposed procedures. A real data set is used to illustrate the procedures. Formulating multivariate meta-analysis as structural equation models provides many new research opportunities for methodological development in both meta-analysis and SEM. Issues related to and extensions on the SEM-based meta-analysis are discussed.  相似文献   

17.
The aims of this study were to present a method for developing a path analytic network model using data acquired from positron emission tomography. Regions of interest within the human brain were identified through quantitative activation likelihood estimation meta-analysis. Using this information, a “true” or population path model was then developed using Bayesian structural equation modeling. To evaluate the impact of sample size on parameter estimation bias, proportion of parameter replication coverage, and statistical power, a 2 group (clinical/control) × 6 (sample size: N = 10, N = 15, N = 20, N = 25, N = 50, N = 100) Markov chain Monte Carlo study was conducted. Results indicate that using a sample size of less than N = 15 per group will produce parameter estimates exhibiting bias greater than 5% and statistical power below .80.  相似文献   

18.
This article investigates likelihood-based difference statistics for testing nonlinear effects in structural equation modeling using the latent moderated structural equations (LMS) approach. In addition to the standard difference statistic TD, 2 robust statistics have been developed in the literature to ensure valid results under the conditions of nonnormality or small sample sizes: the robust TDR and the “strictly positive” TDRP. These robust statistics have not been examined in combination with LMS yet. In 2 Monte Carlo studies we investigate the performance of these methods for testing quadratic or interaction effects subject to different sources of nonnormality, nonnormality due to the nonlinear terms, and nonnormality due to the distribution of the predictor variables. The results indicate that TD is preferable to both TDR and TDRP. Under the condition of strong nonlinear effects and nonnormal predictors, TDR often produced negative differences and TDRP showed no desirable power.  相似文献   

19.
Abstract

Cognitive pattern recognition is known to be an important skill for academic subjects such as mathematics, science, languages, or even humanities. In this study, we investigate the relationships between creativity, critical thinking, and pattern recognition among 203 private school students in Singapore. The instruments used include a creativity test (modified Creativity Selected Elements Questionnaire), a Critical Thinking Test (modified Cornell Critical Thinking), and a pattern recognition test. The main data analysis is done using the SMART-PLS structural equation modeling software. The results of the study reveal that creativity is a weak predictor of pattern recognition (β?=?0.131, p?>?0.05, f2 = 0.024) but critical thinking is a good predictor (β?=?0.517, p?<?0.05, f2 = 0.374). An implication of the research outcome is that more training on critical thinking should be given to the students to improve their pattern recognition ability.  相似文献   

20.
This study investigates effects of early bilingualism on phonological awareness that are abstract and beyond cross-language transfer. It extends the scope of previous research by systematically examining hypotheses derived from structural sensitivity theory. The theory postulates that having access to two languages renders structural similarities and differences between languages more salient, thus allowing bilingual children to form representations of language structure at a more abstract level. About 200 bilingual and monolingual kindergartners, first-graders, and second-graders in Taiwan participated in experiments taking into account the syllable structures, the phoneme inventories, and the phonotactics of the bilinguals' two languages. Findings from the study provide empirical support for structural sensitivity theory and indicate the need to reconceptualize the bilingual effect on metalinguistic development beyond cross-language transfer.  相似文献   

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