Publication:
An alternative matrix transformation to the F test statistic for clustered data

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Issued Date

2019

Resource Type

Article

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application/pdf

ISSN

12347655

DOI

10.21307/stattrans-2019-009

Other identifier(s)

2-s2.0-85068326536

Rights Holder(s)

มหาวิทยาลัยศรีนครินทรวิโรฒ

Bibliographic Citation

Statistics in Transition. Vol 20, No.1 (2019), p.153–169

Suggested Citation

Intarapak S., Supapakorn T. An alternative matrix transformation to the F test statistic for clustered data. Statistics in Transition. Vol 20, No.1 (2019), p.153–169. doi:10.21307/stattrans-2019-009 Retrieved from: https://hdl.handle.net/20.500.14740/5596

Title

An alternative matrix transformation to the F test statistic for clustered data

Author(s)

Intarapak S.
 Supapakorn T.

Abstract

For the regression analysis of clustered data, the error of cluster data violates the independence assumption. Consequently, the test statistic based on the ordinary least square method leads to incorrect inferences. To overcome this issue, the transformation is required to apply to the observations. In this paper we propose an alternative matrix transformation that adjusts the intra-cluster correlation with Householder matrix and apply it to the F test statistic based on generalized least squares procedures for the regression coefficients hypothesis. By Monte Carlo simulations of the balanced and unbalanced data, it is found that the F test statistic based on generalized least squares procedures with Adjusted Householder transformation performs well in terms of the type I error rate and power of the test. © 2019 Glowny Urzad Statystyczny. All rights reserved.

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URI

https://hdl.handle.net/20.500.14740/5596

Collections

Scopus: Year 1983-2021

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