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A comparative study of estimators in multilevel linear models.

ABSTRACT: 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.

SUBMITTER: Ali S

PROVIDER: S-EPMC8601462 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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A comparative study of estimators in multilevel linear models.

Ali Sabz S Shah Said Ali SA Zubair Seema S Hussain Sundas S

PloS one 20211118 11

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 no ...[more]

PMID: 34793510

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