Software implementation of modeling and estimation of effect size in multiple baseline designs
A generalized design-comparable effect size modeling and estimation for multiple baseline designs across individuals has been proposed and evaluated by Restricted Maximum Likelihood method in a hierarchical linear model using R. This report evaluates the exact approach of the modeling and estimation...
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ndltd-UTEXAS-oai-repositories.lib.utexas.edu-2152-240722015-09-20T17:22:35ZSoftware implementation of modeling and estimation of effect size in multiple baseline designsXu, Weiwei, active 2013Effect sizeMultiple baseline designsSingle case studyProc mixedRestricted maximum likelihoodHierachical linear modelProc IMLA generalized design-comparable effect size modeling and estimation for multiple baseline designs across individuals has been proposed and evaluated by Restricted Maximum Likelihood method in a hierarchical linear model using R. This report evaluates the exact approach of the modeling and estimation by SAS. Three models (MB3, MB4 and MB5) with same fixed effects and different random effects are estimated by PROC MIXED procedure with REML method. The unadjusted size and adjusted effect size are then calculated by matrix operation package PROC IML. The estimations for the fixed effects of the three models are similar to each other and to that of R. The variance components estimated by the two software packages are fairly close for MB3 and MB4, but the results are different for MB5 which exhibits boundary conditions for variance-covariance matrix. This result suggests that the nlme library in R works differently than the PROC MIXEDREML method in SAS under extreme conditions.text2014-04-22T15:41:34Z2013-122013-12-17December 20132014-04-22T15:41:34ZThesisapplication/pdfhttp://hdl.handle.net/2152/24072 |
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Effect size Multiple baseline designs Single case study Proc mixed Restricted maximum likelihood Hierachical linear model Proc IML |
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Effect size Multiple baseline designs Single case study Proc mixed Restricted maximum likelihood Hierachical linear model Proc IML Xu, Weiwei, active 2013 Software implementation of modeling and estimation of effect size in multiple baseline designs |
description |
A generalized design-comparable effect size modeling and estimation for multiple baseline designs across individuals has been proposed and evaluated by Restricted Maximum Likelihood method in a hierarchical linear model using R. This report evaluates the exact approach of the modeling and estimation by SAS. Three models (MB3, MB4 and MB5) with same fixed effects and different random effects are estimated by PROC MIXED procedure with REML method. The unadjusted size and adjusted effect size are then calculated by matrix operation package PROC IML. The estimations for the fixed effects of the three models are similar to each other and to that of R. The variance components estimated by the two software packages are fairly close for MB3 and MB4, but the results are different for MB5 which exhibits boundary conditions for variance-covariance matrix. This result suggests that the nlme library in R works differently than the PROC MIXEDREML method in SAS under extreme conditions. === text |
author |
Xu, Weiwei, active 2013 |
author_facet |
Xu, Weiwei, active 2013 |
author_sort |
Xu, Weiwei, active 2013 |
title |
Software implementation of modeling and estimation of effect size in multiple baseline designs |
title_short |
Software implementation of modeling and estimation of effect size in multiple baseline designs |
title_full |
Software implementation of modeling and estimation of effect size in multiple baseline designs |
title_fullStr |
Software implementation of modeling and estimation of effect size in multiple baseline designs |
title_full_unstemmed |
Software implementation of modeling and estimation of effect size in multiple baseline designs |
title_sort |
software implementation of modeling and estimation of effect size in multiple baseline designs |
publishDate |
2014 |
url |
http://hdl.handle.net/2152/24072 |
work_keys_str_mv |
AT xuweiweiactive2013 softwareimplementationofmodelingandestimationofeffectsizeinmultiplebaselinedesigns |
_version_ |
1716823729551441920 |