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Lorah, Julie – Practical Assessment, Research & Evaluation, 2022
Applied educational researchers may be interested in exploring random slope effects in multilevel models, such as when examining individual growth trajectories with longitudinal data. Random slopes are effects for which the slope of an individual-level coefficient varies depending on group membership, however these effects can be difficult to…
Descriptors: Effect Size, Hierarchical Linear Modeling, Longitudinal Studies, Maximum Likelihood Statistics
Wang, Qian – ProQuest LLC, 2022
Over the last four decades, meta-analysis has proven to be a vital analysis strategy in educational research for synthesizing research findings from different studies. When synthesizing studies in a meta-analysis, it is common to assume that the true underlying effect varies from study to study, as studies will differ in design, participants,…
Descriptors: Meta Analysis, Educational Research, Maximum Likelihood Statistics, Statistical Bias
Fangxing Bai; Ben Kelcey – Society for Research on Educational Effectiveness, 2024
Purpose and Background: Despite the flexibility of multilevel structural equation modeling (MLSEM), a practical limitation many researchers encounter is how to effectively estimate model parameters with typical sample sizes when there are many levels of (potentially disparate) nesting. We develop a method-of-moment corrected maximum likelihood…
Descriptors: Maximum Likelihood Statistics, Structural Equation Models, Sample Size, Faculty Development
Bogaert, Jasper; Loh, Wen Wei; Rosseel, Yves – Educational and Psychological Measurement, 2023
Factor score regression (FSR) is widely used as a convenient alternative to traditional structural equation modeling (SEM) for assessing structural relations between latent variables. But when latent variables are simply replaced by factor scores, biases in the structural parameter estimates often have to be corrected, due to the measurement error…
Descriptors: Factor Analysis, Regression (Statistics), Structural Equation Models, Error of Measurement
Sun, Shuyan; Pan, Wei – Journal of Experimental Education, 2013
Regression discontinuity design is an alternative to randomized experiments to make causal inference when random assignment is not possible. This article first presents the formal identification and estimation of regression discontinuity treatment effects in the framework of Rubin's causal model, followed by a thorough literature review of…
Descriptors: Regression (Statistics), Computation, Accuracy, Causal Models
Paek, Insu – ETS Research Report Series, 2009
Three statistical testing procedures well-known in the maximum likelihood approach are the Wald, likelihood ratio (LR), and score tests. Although well-known, the application of these three testing procedures in the logistic regression method to investigate differential item function (DIF) has not been rigorously made yet. Employing a variety of…
Descriptors: Test Bias, Statistical Analysis, Regression (Statistics), Maximum Likelihood Statistics
Brant, Rollin – 1985
Methods for examining the viability of assumptions underlying generalized linear models are considered. By appealing to the likelihood, a natural generalization of the raw residual plot for normal theory models is derived and is applied to investigating potential misspecification of the linear predictor. A smooth version of the plot is also…
Descriptors: Estimation (Mathematics), Generalizability Theory, Goodness of Fit, Mathematical Models

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