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Saijun Zhao; Zhiyong Zhang; Hong Zhang – Grantee Submission, 2024
Mediation analysis is widely applied in various fields of science, such as psychology, epidemiology, and sociology. In practice, many psychological and behavioral phenomena are dynamic, and the corresponding mediation effects are expected to change over time. However, most existing mediation methods assume a static mediation effect over time,…
Descriptors: Bayesian Statistics, Statistical Inference, Longitudinal Studies, Attribution Theory
Saijun Zhao; Zhiyong Zhang; Hong Zhang – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Mediation analysis is widely applied in various fields of science, such as psychology, epidemiology, and sociology. In practice, many psychological and behavioral phenomena are dynamic, and the corresponding mediation effects are expected to change over time. However, most existing mediation methods assume a static mediation effect over time,…
Descriptors: Bayesian Statistics, Statistical Inference, Longitudinal Studies, Attribution Theory
Bayesian Adaptive Lasso for the Detection of Differential Item Functioning in Graded Response Models
Na Shan; Ping-Feng Xu – Journal of Educational and Behavioral Statistics, 2025
The detection of differential item functioning (DIF) is important in psychological and behavioral sciences. Standard DIF detection methods perform an item-by-item test iteratively, often assuming that all items except the one under investigation are DIF-free. This article proposes a Bayesian adaptive Lasso method to detect DIF in graded response…
Descriptors: Bayesian Statistics, Item Response Theory, Adolescents, Longitudinal Studies
Kim, Su-Young; Huh, David; Zhou, Zhengyang; Mun, Eun-Young – International Journal of Behavioral Development, 2020
Latent growth models (LGMs) are an application of structural equation modeling and frequently used in developmental and clinical research to analyze change over time in longitudinal outcomes. Maximum likelihood (ML), the most common approach for estimating LGMs, can fail to converge or may produce biased estimates in complex LGMs especially in…
Descriptors: Bayesian Statistics, Maximum Likelihood Statistics, Longitudinal Studies, Models
Zhan, Peida; He, Keren – Educational Measurement: Issues and Practice, 2021
In learning diagnostic assessments, the attribute hierarchy specifies a sequential network of interrelated attribute mastery processes, which makes a test blueprint consistent with the cognitive theory. One of the most important functions of attribute hierarchy is to guide or limit the developmental direction of students and then form a…
Descriptors: Longitudinal Studies, Models, Comparative Analysis, Diagnostic Tests
Kirksey, J. Jacob; Gottfried, Michael A. – Journal of Research on Educational Effectiveness, 2021
Over the past decade, identifying how schools might reduce student absenteeism has moved to the forefront of education policy. Yet little research has examined whether school type itself is important. We focus on the influence of Catholic schools using data from the past decade--the most relevant policy context for addressing absenteeism. The…
Descriptors: Educational Policy, Attendance, Catholic Schools, Institutional Characteristics
Kim, Jungnam; Bryan, Julia Green; Griffin, Dana; Sharma, Gitima – Journal of Multicultural Counseling and Development, 2022
We investigated the relationship between Asian parent empowerment and their children's college enrollment in a sample of 357 Asian parents from various ethnic subgroups using the High School Longitudinal Study 2009. A multinomial logistic regression indicated differences in Asian students' college enrollment by ethnic subgroup and income and in…
Descriptors: Models, Minority Group Students, Asian Americans, Stereotypes
Wang, Chun; Nydick, Steven W. – Journal of Educational and Behavioral Statistics, 2020
Recent work on measuring growth with categorical outcome variables has combined the item response theory (IRT) measurement model with the latent growth curve model and extended the assessment of growth to multidimensional IRT models and higher order IRT models. However, there is a lack of synthetic studies that clearly evaluate the strength and…
Descriptors: Item Response Theory, Longitudinal Studies, Comparative Analysis, Models
Hasenäcker, Jana; Schroeder, Sascha – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2022
Reading development involves several changes in orthographic processing. A key question is, "how does the coding of letters develops in children learning to read?" Masked priming effects of transposition and substitution primes have been taken to index the importance of letter position and identity coding. Somewhat contradicting results…
Descriptors: Alphabets, Reading Processes, Priming, Longitudinal Studies
Duxbury, Scott W. – Sociological Methods & Research, 2023
This study shows that residual variation can cause problems related to scaling in exponential random graph models (ERGM). Residual variation is likely to exist when there are unmeasured variables in a model--even those uncorrelated with other predictors--or when the logistic form of the model is inappropriate. As a consequence, coefficients cannot…
Descriptors: Graphs, Scaling, Research Problems, Models
Madison, Matthew J. – Educational Measurement: Issues and Practice, 2019
Recent advances have enabled diagnostic classification models (DCMs) to accommodate longitudinal data. These longitudinal DCMs were developed to study how examinees change, or transition, between different attribute mastery statuses over time. This study examines using longitudinal DCMs as an approach to assessing growth and serves three purposes:…
Descriptors: Longitudinal Studies, Item Response Theory, Psychometrics, Criterion Referenced Tests
Ning, Ling; Luo, Wen – Journal of Experimental Education, 2018
Piecewise GMM with unknown turning points is a new procedure to investigate heterogeneous subpopulations' growth trajectories consisting of distinct developmental phases. Unlike the conventional PGMM, which relies on theory or experiment design to specify turning points a priori, the new procedure allows for an optimal location of turning points…
Descriptors: Statistical Analysis, Models, Classification, Comparative Analysis
Vogels, Jorrig; Lindgren, Josefin – Discourse Processes: A Multidisciplinary Journal, 2022
When telling a story, a speaker needs to refer to story characters using appropriate expressions, which requires a mental model of the discourse. We hypothesize that, compared to those of adults, children's discourse models are based more on factors that are less cognitively demanding, such as animacy, and as they grow older, discourse factors…
Descriptors: Swedish, Preschool Children, Discourse Analysis, Cues
Wang, Chun; Nydick, Steven W. – Grantee Submission, 2019
Recent work on measuring growth with categorical outcome variables has combined the item response theory (IRT) measurement model with the latent growth curve (LGC) model (e.g., McArdle, 1988) and extended the assessment of growth to multidimensional IRT models (e.g., Hsieh, von Eye, & Maier, 2010; Huang, 2013) and higher-order IRT models…
Descriptors: Longitudinal Studies, Item Response Theory, Comparative Analysis, Models
Xiao, Bowen; Bullock, Amanda; Liu, Junsheng; Coplan, Robert – Journal of Early Adolescence, 2021
In this study, we explored the longitudinal linkages among Chinese early adolescents' unsociability, peer rejection, and loneliness. Participants were N = 445 primary school students in Shanghai, P.R. China followed over 3 years from Grades 6 and 7 to Grades 8 and 9. Measures of adolescents' unsociability, peer rejection, and loneliness were…
Descriptors: Peer Acceptance, Rejection (Psychology), Psychological Patterns, Early Adolescents