Fixed Effects or Mixed Effects Classifiers? Evidence From Simulated and Archival Data.
This study seeks to compare fixed and mixed effects models for the purposes of predictive classification in the presence of multilevel data. The first part of the study utilizes a Monte Carlo simulation to compare fixed and mixed effects logistic regression and random forests. An applied examination...
| Publicado en: | Educational & Psychological Measurement Vol. 83; no. 4; pp. 710 - 740 |
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| Autores principales: | , , |
| Formato: | Artículo |
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Sage Publications Inc.
Aug2023
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=164375402&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 164375402 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00131644 EPM jtl: Educational & Psychological Measurement issn: 00131644 maglogo: Y pubinfo: dt: Aug2023 vid: 83 iid: 4 pid: 344 pub: Sage Publications Inc. artinfo: ui: 164375402 10.1177/00131644221108180 ppf: 710 ppct: 30 formats: tig: atl: Fixed Effects or Mixed Effects Classifiers? Evidence From Simulated and Archival Data. aug: au: Mangino, Anthony A. Bolin, Jocelyn H. Finch, W. Holmes affil: Ball State University, Muncie, IN, USA University of Kentucky, Lexington, USA su: Analysis of variance Educational tests & measurements Academic achievement Students Multivariate analysis Simulation methods in education Random forest algorithms Database management School holding power Intraclass correlation Research funding Statistical models Logistic regression analysis Cluster analysis (Statistics) Data analysis software Receiver operating characteristic curves sug: subj: Analysis of variance Educational tests & measurements Academic achievement Students Data Processing, Hosting, and Related Services Multivariate analysis Simulation methods in education Random forest algorithms Database management School holding power Intraclass correlation Research funding Statistical models Logistic regression analysis Cluster analysis (Statistics) Data analysis software Receiver operating characteristic curves keyword: mixed effects models Monte Carlo simulation predictive classification Program for International Student Assessment mixed effects models Monte Carlo simulation predictive classification Program for International Student Assessment ab: This study seeks to compare fixed and mixed effects models for the purposes of predictive classification in the presence of multilevel data. The first part of the study utilizes a Monte Carlo simulation to compare fixed and mixed effects logistic regression and random forests. An applied examination of the prediction of student retention in the public-use U.S. PISA data set was considered to verify the simulation findings. Results of this study indicate fixed effects models performed comparably with mixed effects models across both the simulation and PISA examinations. Results broadly suggest that researchers should be cognizant of the type of predictors and data structure being used, as these factors carried more weight than did the model type. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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