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Dae Woong Ham; Luke Miratrix – Grantee Submission, 2024
The consequence of a change in school leadership (e.g., principal turnover) on student achievement has important implications for education policy. The impact of such an event can be estimated via the popular Difference in Difference (DiD) estimator, where those schools with a turnover event are compared to a selected set of schools that did not…
Descriptors: Trend Analysis, Faculty Mobility, Academic Achievement, Principals
Michael C. Robbins; Zhuping Li – Field Methods, 2025
The Nolan Index (NI) is a normed, quantitative measure for comparing the degree of resemblance (similarity or dissimilarity) between free listings with an Excel program for calculating it. This article enhances that effort with the addition of an R program and additional applications. Free-list resemblance measures have been used to investigate…
Descriptors: Computation, Norm Referenced Tests, Comparative Analysis, Spreadsheets
Suyoung Kim; Sooyong Lee; Jiwon Kim; Tiffany A. Whittaker – Structural Equation Modeling: A Multidisciplinary Journal, 2024
This study aims to address a gap in the social and behavioral sciences literature concerning interaction effects between latent factors in multiple-group analysis. By comparing two approaches for estimating latent interactions within multiple-group analysis frameworks using simulation studies and empirical data, we assess their relative merits.…
Descriptors: Social Science Research, Behavioral Sciences, Structural Equation Models, Statistical Analysis
Han Du; Brian Keller; Egamaria Alacam; Craig Enders – Grantee Submission, 2023
In Bayesian statistics, the most widely used criteria of Bayesian model assessment and comparison are Deviance Information Criterion (DIC) and Watanabe-Akaike Information Criterion (WAIC). A multilevel mediation model is used as an illustrative example to compare different types of DIC and WAIC. More specifically, the study compares the…
Descriptors: Bayesian Statistics, Models, Comparative Analysis, Probability
Breen, Richard; Bernt Karlson, Kristian; Holm, Anders – Sociological Methods & Research, 2021
The Karlson-Holm-Breen (KHB) method has rapidly become popular as a way of separating the impact of confounding from rescaling when comparing conditional and unconditional parameter estimates in nonlinear probability models such as the logit and probit. In this note, we show that the same estimates can be obtained in a somewhat different way to…
Descriptors: Probability, Models, Computation, Comparative Analysis
Lemonidis, Charalampos; Likidis, Nikos – International Journal of Mathematical Education in Science and Technology, 2021
In this study, we propose an integrated hierarchical model of computational estimation strategies (IHMCES), which can be used to organize a set of computational estimation strategies, used by a group of individuals, in strategy ranges. IHMCES can be used for the description of the repertoire, profile and flexibility of individuals regarding the…
Descriptors: Mathematics Instruction, Teaching Methods, Grade 5, Elementary School Students
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
Schulte, Ann C.; Stevens, Joseph J.; Nese, Joseph F. T.; Yel, Nedim; Tindal, Gerald; Elliott, Stephen N. – National Center on Assessment and Accountability for Special Education, 2018
This technical report is one of a series of four technical reports that describe the results of a study comparing eight alternative models for estimating school academic achievement using data from the Arizona, North Carolina, Oregon, and Pennsylvania accountability systems. The purpose of these reports was to evaluate a broad range of models…
Descriptors: School Effectiveness, Models, Computation, Comparative Analysis
Nese, Joseph F. T.; Stevens, Joseph J.; Schulte, Ann C.; Tindal, Gerald; Yel, Nedim; Anderson, Daniel; Matta, Tyler; Elliott, Stephen N. – National Center on Assessment and Accountability for Special Education, 2018
This technical report is one of a series of four technical reports that describe the results of a study comparing eight alternative models for estimating school academic achievement using data from the Arizona, North Carolina, Oregon, and Pennsylvania accountability systems. The purpose of these reports was to evaluate a broad range of models…
Descriptors: School Effectiveness, Models, Computation, Comparative Analysis
Hsiao, Yu-Yu; Kwok, Oi-Man; Lai, Mark H. C. – Educational and Psychological Measurement, 2018
Path models with observed composites based on multiple items (e.g., mean or sum score of the items) are commonly used to test interaction effects. Under this practice, researchers generally assume that the observed composites are measured without errors. In this study, we reviewed and evaluated two alternative methods within the structural…
Descriptors: Error of Measurement, Testing, Scores, Models
Gurkan, Gulsah; Benjamini, Yoav; Braun, Henry – Large-scale Assessments in Education, 2021
Employing nested sequences of models is a common practice when exploring the extent to which one set of variables mediates the impact of another set. Such an analysis in the context of logistic regression models confronts two challenges: (1) direct comparisons of coefficients across models are generally biased due to the changes in scale that…
Descriptors: Statistical Inference, Regression (Statistics), Adults, Models
Huang, Jiajing; Liang, Xinya; Yang, Yanyun – AERA Online Paper Repository, 2017
In Bayesian structural equation modeling (BSEM), prior settings may affect model fit, parameter estimation, and model comparison. This simulation study was to investigate how the priors impact evaluation of relative fit across competing models. The design factors for data generation included sample sizes, factor structures, data distributions, and…
Descriptors: Bayesian Statistics, Structural Equation Models, Goodness of Fit, Sample Size
Stevens, Joseph J.; Nese, Joseph F. T.; Schulte, Ann C.; Tindal, Gerald; Yel, Nedim; Anderson, Daniel; Matta, Tyler; Elliott, Stephen N. – National Center on Assessment and Accountability for Special Education, 2017
This technical report is one of a series of four technical reports that describe the results of a study comparing eight alternative models for estimating school academic achievement using data from the Arizona, North Carolina, Oregon, and Pennsylvania accountability systems. The purpose of these reports was to evaluate a broad range of models…
Descriptors: School Effectiveness, Models, Computation, Comparative Analysis
Schulte, Ann C.; Nese, Joseph F. T.; Stevens, Joseph J.; Yel, Nedim; Tindal, Gerald; Anderson, Daniel; Elliott, Stephen N. – National Center on Assessment and Accountability for Special Education, 2017
This technical report is one of a series of four technical reports that describe the results of a study comparing eight alternative models for estimating school academic achievement using data from the Arizona, North Carolina, Oregon, and Pennsylvania accountability systems. The purpose of these reports was to evaluate a broad range of models…
Descriptors: School Effectiveness, Models, Computation, Comparative Analysis
Soland, James; Thum, Yeow Meng – Journal of Research on Educational Effectiveness, 2022
Sources of longitudinal achievement data are increasing thanks partially to the expansion of available interim assessments. These tests are often used to monitor the progress of students, classrooms, and schools within and across school years. Yet, few statistical models equipped to approximate the distinctly seasonal patterns in the data exist,…
Descriptors: Academic Achievement, Longitudinal Studies, Data Use, Computation