A comparative study of estimators in multilevel linear models

Multilevel Models are widely used in organizational research, educational research, epidemiology, psychology, biology and medical fields. In this paper, we recommend the situations where Bootstrap procedures through Minimum Norm Quadratic Unbiased Estimator (MINQUE) can be extremely handy than that...

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Autores principales:	Sabz Ali, Said Ali Shah, Seema Zubair, Sundas Hussain
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/319caf8bc6ff42809a509ec408050a21
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spelling	oai:doaj.org-article:319caf8bc6ff42809a509ec408050a212021-11-25T06:19:41ZA comparative study of estimators in multilevel linear models1932-6203https://doaj.org/article/319caf8bc6ff42809a509ec408050a212021-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8601462/?tool=EBIhttps://doaj.org/toc/1932-6203Multilevel Models are widely used in organizational research, educational research, epidemiology, psychology, biology and medical fields. In this paper, we recommend the situations where Bootstrap procedures through Minimum Norm Quadratic Unbiased Estimator (MINQUE) can be extremely handy than that of Restricted Maximum Likelihood (REML) in multilevel level linear regression models. In our simulation study the bootstrap by means of MINQUE is superior to REML in conditions where normality does not hold. Moreover, the real data application also supports our findings in terms of accuracy of estimates and their standard errors.Sabz AliSaid Ali ShahSeema ZubairSundas HussainPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 11 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Sabz Ali Said Ali Shah Seema Zubair Sundas Hussain A comparative study of estimators in multilevel linear models
description	Multilevel Models are widely used in organizational research, educational research, epidemiology, psychology, biology and medical fields. In this paper, we recommend the situations where Bootstrap procedures through Minimum Norm Quadratic Unbiased Estimator (MINQUE) can be extremely handy than that of Restricted Maximum Likelihood (REML) in multilevel level linear regression models. In our simulation study the bootstrap by means of MINQUE is superior to REML in conditions where normality does not hold. Moreover, the real data application also supports our findings in terms of accuracy of estimates and their standard errors.
format	article
author	Sabz Ali Said Ali Shah Seema Zubair Sundas Hussain
author_facet	Sabz Ali Said Ali Shah Seema Zubair Sundas Hussain
author_sort	Sabz Ali
title	A comparative study of estimators in multilevel linear models
title_short	A comparative study of estimators in multilevel linear models
title_full	A comparative study of estimators in multilevel linear models
title_fullStr	A comparative study of estimators in multilevel linear models
title_full_unstemmed	A comparative study of estimators in multilevel linear models
title_sort	comparative study of estimators in multilevel linear models
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/319caf8bc6ff42809a509ec408050a21
work_keys_str_mv	AT sabzali acomparativestudyofestimatorsinmultilevellinearmodels AT saidalishah acomparativestudyofestimatorsinmultilevellinearmodels AT seemazubair acomparativestudyofestimatorsinmultilevellinearmodels AT sundashussain acomparativestudyofestimatorsinmultilevellinearmodels AT sabzali comparativestudyofestimatorsinmultilevellinearmodels AT saidalishah comparativestudyofestimatorsinmultilevellinearmodels AT seemazubair comparativestudyofestimatorsinmultilevellinearmodels AT sundashussain comparativestudyofestimatorsinmultilevellinearmodels
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A comparative study of estimators in multilevel linear models

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