File Download
Supplementary

Conference Paper: Regression Towards the Mean Artifacts and Matthew Effects in multilevel analyses of value-added of individual schools

TitleRegression Towards the Mean Artifacts and Matthew Effects in multilevel analyses of value-added of individual schools
Authors
Issue Date2005
PublisherThe Australian Association for Research in Education
Citation
The Australian Association for Research in Education Annual Conference, 2005 How to Cite?
AbstractLeague tables are a problematic approach to inferring school effectiveness, but traditional value-added approaches are fraught with statistical complexities. According to the Regression Towards the Mean Artifacts (RTMA), students with initially high or low scores tend to regress towards the mean in subsequent testing, resulting in biased estimates of school growth (Marsh & Hau, 2002). The Matthews Effect is an apparently counter-balancing artifact in growth in achievement gains is systematically larger for students who are initially more able. (i.e., the rich becomes richer). Mathematical proof shows that although the Matthew and the RTMA artifacts work in opposite direction and tend to cancel each other, they share a similar mechanism and can be rectified. In this study, mathematical derivations and Monte Carlo simulated data are used to compare four models, namely: (i) without any remedy, (ii) with remedy for Matthew effect only, (iii) with remedy for RTMA only, (iv) remedies for both Matthew and RTMA effects. The conditional strategy with individual assignment test scores (used in assigning students to different schools) as covariate remedies artifacts, consistent with Marsh & Hau's (2002) conclusion for RTMA. The associated problems with the two effects in estimating school value-added information are discussed.
Persistent Identifierhttp://hdl.handle.net/10722/109945

 

DC FieldValueLanguage
dc.contributor.authorLi, Xen_HK
dc.contributor.authorMarsh, HWen_HK
dc.contributor.authorHau, KTen_HK
dc.contributor.authorHo, ITFen_HK
dc.contributor.authorMartin, AJen_HK
dc.date.accessioned2010-09-26T01:44:06Z-
dc.date.available2010-09-26T01:44:06Z-
dc.date.issued2005en_HK
dc.identifier.citationThe Australian Association for Research in Education Annual Conference, 2005-
dc.identifier.urihttp://hdl.handle.net/10722/109945-
dc.description.abstractLeague tables are a problematic approach to inferring school effectiveness, but traditional value-added approaches are fraught with statistical complexities. According to the Regression Towards the Mean Artifacts (RTMA), students with initially high or low scores tend to regress towards the mean in subsequent testing, resulting in biased estimates of school growth (Marsh & Hau, 2002). The Matthews Effect is an apparently counter-balancing artifact in growth in achievement gains is systematically larger for students who are initially more able. (i.e., the rich becomes richer). Mathematical proof shows that although the Matthew and the RTMA artifacts work in opposite direction and tend to cancel each other, they share a similar mechanism and can be rectified. In this study, mathematical derivations and Monte Carlo simulated data are used to compare four models, namely: (i) without any remedy, (ii) with remedy for Matthew effect only, (iii) with remedy for RTMA only, (iv) remedies for both Matthew and RTMA effects. The conditional strategy with individual assignment test scores (used in assigning students to different schools) as covariate remedies artifacts, consistent with Marsh & Hau's (2002) conclusion for RTMA. The associated problems with the two effects in estimating school value-added information are discussed.-
dc.languageengen_HK
dc.publisherThe Australian Association for Research in Education-
dc.relation.ispartofThe Australian Association for Research in Education Annual Conferenceen_HK
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.titleRegression Towards the Mean Artifacts and Matthew Effects in multilevel analyses of value-added of individual schoolsen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailHo, ITF: itfho@hkucc.hku.hken_HK
dc.identifier.authorityHo, ITF=rp00556en_HK
dc.description.naturepublished_or_final_version-
dc.identifier.hkuros123644en_HK

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats