Modeling achievement in the presence of student mobility : a growth curve model for multiple membership data
The current study evaluated a multiple-membership growth curve model that can be used to model growth in student achievement, in the presence of student mobility. The purpose of the study was to investigate the impact of ignoring multiple school membership when modeling student achievement across ti...
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ndltd-UTEXAS-oai-repositories.lib.utexas.edu-2152-ETD-UT-2010-08-16322015-09-20T16:56:13ZModeling achievement in the presence of student mobility : a growth curve model for multiple membership dataGrady, Matthew William, 1981-Growth curve modelingStudent mobilityStudent achievementAcademic achievementThe current study evaluated a multiple-membership growth curve model that can be used to model growth in student achievement, in the presence of student mobility. The purpose of the study was to investigate the impact of ignoring multiple school membership when modeling student achievement across time. Part one of the study consisted of an analysis of real longitudinal student achievement data. This real data analysis compared parameter estimates, standard error estimates, and model-fit statistics obtained from a growth curve model that ignores multiple membership, to those obtained from a growth model that accounts for multiple school membership via the MMREM approach. Part two of the study consisted of a simulation study designed to determine the impact of ignoring multiple membership and the accuracy of parameter estimates obtained under the two modeling approaches, under a series of data conditions. The goal of the study was to assess the importance of incorporating a more flexible MMREM approach when modeling students’ academic achievement across time. Overall, the results of the current study indicated that the Cross-classified multiple membership growth curve model (CCMM-GCM) may provide more accurate parameter estimates than competing approaches for a number of data conditions. Both modeling approaches, however, yielded substantially biased estimates of parameters for some experimental conditions. Overall, results demonstrate that incorporating student mobility into achievement growth modeling can result in more accurate estimates of schools effects.text2010-12-03T20:59:46Z2010-12-03T20:59:52Z2010-12-03T20:59:46Z2010-12-03T20:59:52Z2010-082010-12-03August 20102010-12-03T20:59:52Zthesisapplication/pdfhttp://hdl.handle.net/2152/ETD-UT-2010-08-1632eng |
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Others
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Growth curve modeling Student mobility Student achievement Academic achievement |
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Growth curve modeling Student mobility Student achievement Academic achievement Grady, Matthew William, 1981- Modeling achievement in the presence of student mobility : a growth curve model for multiple membership data |
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The current study evaluated a multiple-membership growth curve model that can be used to model growth in student achievement, in the presence of student mobility. The purpose of the study was to investigate the impact of ignoring multiple school membership when modeling student achievement across time. Part one of the study consisted of an analysis of real longitudinal student achievement data. This real data analysis compared parameter estimates, standard error estimates, and model-fit statistics obtained from a growth curve model that ignores multiple membership, to those obtained from a growth model that accounts for multiple school membership via the MMREM approach. Part two of the study consisted of a simulation study designed to determine the impact of ignoring multiple membership and the accuracy of parameter estimates obtained under the two modeling approaches, under a series of data conditions. The goal of the study was to assess the importance of incorporating a more flexible MMREM approach when modeling students’ academic achievement across time. Overall, the results of the current study indicated that the Cross-classified multiple membership growth curve model (CCMM-GCM) may provide more accurate parameter estimates than competing approaches for a number of data conditions. Both modeling approaches, however, yielded substantially biased estimates of parameters for some experimental conditions. Overall, results demonstrate that incorporating student mobility into achievement growth modeling can result in more accurate estimates of schools effects. === text |
author |
Grady, Matthew William, 1981- |
author_facet |
Grady, Matthew William, 1981- |
author_sort |
Grady, Matthew William, 1981- |
title |
Modeling achievement in the presence of student mobility : a growth curve model for multiple membership data |
title_short |
Modeling achievement in the presence of student mobility : a growth curve model for multiple membership data |
title_full |
Modeling achievement in the presence of student mobility : a growth curve model for multiple membership data |
title_fullStr |
Modeling achievement in the presence of student mobility : a growth curve model for multiple membership data |
title_full_unstemmed |
Modeling achievement in the presence of student mobility : a growth curve model for multiple membership data |
title_sort |
modeling achievement in the presence of student mobility : a growth curve model for multiple membership data |
publishDate |
2010 |
url |
http://hdl.handle.net/2152/ETD-UT-2010-08-1632 |
work_keys_str_mv |
AT gradymatthewwilliam1981 modelingachievementinthepresenceofstudentmobilityagrowthcurvemodelformultiplemembershipdata |
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1716821154061090816 |