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Yuan Fang; Lijuan Wang – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Dynamic structural equation modeling (DSEM) is a useful technique for analyzing intensive longitudinal data. A challenge of applying DSEM is the missing data problem. The impact of missing data on DSEM, especially on widely applied DSEM such as the two-level vector autoregressive (VAR) cross-lagged models, however, is understudied. To fill the…
Descriptors: Structural Equation Models, Bayesian Statistics, Monte Carlo Methods, Longitudinal Studies
Shen, Ting; Konstantopoulos, Spyros – Journal of Experimental Education, 2022
Large-scale education data are collected via complex sampling designs that incorporate clustering and unequal probability of selection. Multilevel models are often utilized to account for clustering effects. The probability weighted approach (PWA) has been frequently used to deal with the unequal probability of selection. In this study, we examine…
Descriptors: Data Collection, Educational Research, Hierarchical Linear Modeling, Bayesian Statistics
Sainan Xu; Jing Lu; Jiwei Zhang; Chun Wang; Gongjun Xu – Grantee Submission, 2024
With the growing attention on large-scale educational testing and assessment, the ability to process substantial volumes of response data becomes crucial. Current estimation methods within item response theory (IRT), despite their high precision, often pose considerable computational burdens with large-scale data, leading to reduced computational…
Descriptors: Educational Assessment, Bayesian Statistics, Statistical Inference, Item Response Theory
Sarafoglou, Alexandra; van der Heijden, Anna; Draws, Tim; Cornelisse, Joran; Wagenmakers, Eric-Jan; Marsman, Maarten – Psychology Learning and Teaching, 2022
Current developments in the statistics community suggest that modern statistics education should be structured holistically, that is, by allowing students to work with real data and to answer concrete statistical questions, but also by educating them about alternative frameworks, such as Bayesian inference. In this article, we describe how we…
Descriptors: Bayesian Statistics, Thinking Skills, Undergraduate Students, Psychology
Randall, David; Welser, Christopher – National Association of Scholars, 2018
A reproducibility crisis afflicts a wide range of scientific and social-scientific disciplines, from epidemiology to social psychology. Improper research techniques, lack of accountability, disciplinary and political groupthink, and a scientific culture biased toward producing positive results together have produced a critical state of affairs.…
Descriptors: Scientific Methodology, Replication (Evaluation), Scientific Research, Guidelines
Kaplan, David; McCarty, Alyn Turner – Large-scale Assessments in Education, 2013
Background: In the context of international large scale assessments, it is often not feasible to implement a complete survey of all relevant populations. For example, the OECD Program for International Student Assessment surveys both students and schools, but does not obtain information from teachers. In contrast the OECD Teaching and Learning…
Descriptors: Measurement, International Assessment, Student Surveys, Teacher Surveys
Maxwell, Martha – 1998
Simple Bayesian approaches can be applied to answer specific questions in evaluating an individualized reading program. A small reading and study skills program located in the counseling center of a major research university collected and compiled data on student characteristics such as class, number of sessions attended, grade point average, and…
Descriptors: Bayesian Statistics, Data Collection, Decision Making, Higher Education