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Showing all 13 results Save | Export
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Ke-Hai Yuan; Ling Ling; Zhiyong Zhang – Grantee Submission, 2024
Data in social and behavioral sciences typically contain measurement errors and do not have predefined metrics. Structural equation modeling (SEM) is widely used for the analysis of such data, where the scales of the manifest and latent variables are often subjective. This article studies how the model, parameter estimates, their standard errors…
Descriptors: Structural Equation Models, Computation, Social Science Research, Error of Measurement
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Ke-Hai Yuan; Ling Ling; Zhiyong Zhang – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Data in social and behavioral sciences typically contain measurement errors and do not have predefined metrics. Structural equation modeling (SEM) is widely used for the analysis of such data, where the scales of the manifest and latent variables are often subjective. This article studies how the model, parameter estimates, their standard errors…
Descriptors: Structural Equation Models, Computation, Social Science Research, Error of Measurement
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Xiaying Zheng; Ji Seung Yang; Jeffrey R. Harring – Structural Equation Modeling: A Multidisciplinary Journal, 2022
Measuring change in an educational or psychological construct over time is often achieved by repeatedly administering the same items to the same examinees over time and fitting a second-order latent growth curve model. However, latent growth modeling with full information maximum likelihood (FIML) estimation becomes computationally challenging…
Descriptors: Longitudinal Studies, Data Analysis, Item Response Theory, Structural Equation Models
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Zhang, Zhiyong; Wang, Lijuan – Psychometrika, 2013
Despite wide applications of both mediation models and missing data techniques, formal discussion of mediation analysis with missing data is still rare. We introduce and compare four approaches to dealing with missing data in mediation analysis including list wise deletion, pairwise deletion, multiple imputation (MI), and a two-stage maximum…
Descriptors: Maximum Likelihood Statistics, Structural Equation Models, Simulation, Measurement Techniques
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Pietarinen, Janne; Pyhältö, Kirsi; Soini, Tiina – Curriculum Journal, 2017
The study aims to gain a better understanding of the national large-scale curriculum process in terms of the used implementation strategies, the function of the reform, and the curriculum coherence perceived by the stakeholders accountable in constructing the national core curriculum in Finland. A large body of school reform literature has shown…
Descriptors: Foreign Countries, Educational Change, Curriculum Implementation, Educational Strategies
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Blozis, Shelley A.; Ge, Xiaojia; Xu, Shu; Natsuaki, Misaki N.; Shaw, Daniel S.; Neiderhiser, Jenae M.; Scaramella, Laura V.; Leve, Leslie D.; Reiss, David – Structural Equation Modeling: A Multidisciplinary Journal, 2013
Missing data are common in studies that rely on multiple informant data to evaluate relationships among variables for distinguishable individuals clustered within groups. Estimation of structural equation models using raw data allows for incomplete data, and so all groups can be retained for analysis even if only 1 member of a group contributes…
Descriptors: Data, Structural Equation Models, Correlation, Data Analysis
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Morris, R. C. – Current Issues in Education, 2016
Higher education research highlights the difficulties students face when transitioning from a junior college to a traditional university. This study explored a gap between junior vs. traditional university students' academic self-efficacy beliefs. This study also controlled for the effects of the student role-identity and academic performance on…
Descriptors: Self Efficacy, Two Year Colleges, College Students, Higher Education
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McArdle, John J.; Hamagami, Fumiaki; Bautista, Randy; Onoye, Jane; Hishinuma, Earl S.; Prescott, Carol A.; Takeshita, Junji; Zonderman, Alan B.; Johnson, Ronald C. – Educational and Psychological Measurement, 2014
In this study, we reanalyzed the classic Hawai'i Family Study of Cognition (HFSC) data using contemporary multilevel modeling techniques. We used the HFSC baseline data ("N" = 6,579) and reexamined the factorial structure of 16 cognitive variables using confirmatory (restricted) measurement models in an explicit sequence. These models…
Descriptors: Factor Analysis, Hierarchical Linear Modeling, Data Analysis, Structural Equation Models
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Powell, Brett A.; Gilleland, Diane Suitt; Pearson, L. Carolyn – Journal of Higher Education, 2012
Institutions of higher education are under pressure to be accountable for their expenditures while demonstrating their effectiveness. Through structural equation modeling, a relationship was found between expenditures and the efficiency and effectiveness of an institution, and an optimal expenditure level was found that maximized an institution's…
Descriptors: Expenditures, Efficiency, Benchmarking, Models
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Lee, In Heok – Career and Technical Education Research, 2012
Researchers in career and technical education often ignore more effective ways of reporting and treating missing data and instead implement traditional, but ineffective, missing data methods (Gemici, Rojewski, & Lee, 2012). The recent methodological, and even the non-methodological, literature has increasingly emphasized the importance of…
Descriptors: Vocational Education, Data Collection, Maximum Likelihood Statistics, Educational Research
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Savalei, Victoria – Structural Equation Modeling: A Multidisciplinary Journal, 2008
Normal theory maximum likelihood (ML) is by far the most popular estimation and testing method used in structural equation modeling (SEM), and it is the default in most SEM programs. Even though this approach assumes multivariate normality of the data, its use can be justified on the grounds that it is fairly robust to the violations of the…
Descriptors: Structural Equation Models, Testing, Factor Analysis, Maximum Likelihood Statistics
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Zimmer-Gembeck, Melanie J.; Chipuer, Heather M.; Hanisch, Michelle; Creed, Peter A.; McGregor, Leanne – Journal of Adolescence, 2006
Guided by Self-Determination and associated theories, we examined whether adolescent (N=324, Mage=15, 52% female) competence (academic engagement and achievement) were supported by relationships at school and school fit. Aspects of relationships and school fit that were measured included adolescents' perceptions of each context as promoting…
Descriptors: Intervals, Structural Equation Models, Academic Achievement, Self Determination
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Carter, Rufus Lynn – Research & Practice in Assessment, 2006
Many times in both educational and social science research it is impossible to collect data that is complete. When administering a survey, for example, people may answer some questions and not others. This missing data causes a problem for researchers using structural equation modeling (SEM) techniques for data analyses. Because SEM and…
Descriptors: Structural Equation Models, Error of Measurement, Data, Change Strategies