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

100%

Intarapak S., Supapakorn T.

Statistics in Transition new series

2019

vol. 20

issue 1

153-169

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.

Comparison of confidence intervals for variance components in an unbalanced one-way random effects model

81%

Jiratampradab A., Supapakorn T., Suntornchost J.

Statistics in Transition new series

2022

vol. 23

issue 4

149-160

The purpose of this paper is to study and compare the methods for constructing confidence intervals for variance components in an unbalanced one-way random effects model. The methods are based on a classical exact, generalised pivotal quantity, a fiducial inference and a fiducial generalised pivotal quantity. The comparison of criteria involves the empirical coverage probability that maintains at the nominal confidence level of 0.95 and the shortest average length of the confidence interval. The simulation results show that the method based on the generalised pivotal quantity and the fiducial inference perform very well in terms of both the empirical coverage probability and the average length of the confidence interval. The classical exact method performs well in some situations, while the fiducial generalised pivotal quantity performs well in a very unbalanced design. Therefore, the method based on the generalised pivotal quantity is recommended for all situations.

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2 Statistics in Transition new series

2 Supapakorn T.

1 Intarapak S.

1 Jiratampradab A.

1 Suntornchost J.

1 2022

1 2019

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

Comparison of confidence intervals for variance components in an unbalanced one-way random effects model