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Autor
Intarapak Sukanya (Srinakharinwirot University, Bangkok, Thailand), Supapakorn Thidaporn (Kasetsart University, Bangkok, Thailand)
Tytuł
An Alternative Matrix Transformation to the F Test Statistic for Clustered Data
Źródło
Statistics in Transition, 2019, vol. 20, nr 1, s. 153-174, rys., tab., aneks, bibliogr. s. 167-168
Słowa kluczowe
Metoda najmniejszych kwadratów, Macierze
Least squares method, Matrix
Uwagi
summ.
Abstrakt
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. (original abstract)
Dostępne w
Biblioteka Główna Uniwersytetu Ekonomicznego w Krakowie
Biblioteka SGH im. Profesora Andrzeja Grodka
Biblioteka Główna Uniwersytetu Ekonomicznego w Katowicach
Pełny tekst
Pokaż
Bibliografia
Pokaż
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  6. HOUSEHOLDER, A. S., (1958). Unitary Triangularization of a Nonsymmetric Matrix. Journal of the ACM, 5, pp. 339-342.
  7. LAHIRI, P., LI, Y., (2009). A New Alternative to the Standard F Test for Clustered Data. Journal of Statistical Planning and Inference, 139, pp. 3430-3441.
  8. LANCASTER, H. O., (1965). The Helmert Matrices. The American Mathematical Monthly, 72, pp. 4-12.
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  10. MIALL, W. E., OLDHAM, P. D., (1955). A Study of Arterial Blood Pressure and Its Inheritance in a Sample of the General Population. Clinical Science, 14 (3), pp. 459-488.
  11. NG, S. K., MCLACHLAN, G. J., YAU, K. K. W., LEE, A. H., (2004). Modeling the Distribution of Ischaemic Stroke-specific Survival Time using an EM-based Mixture Approach with Random Effects Adjustment. Statistics in Medicine, 23, pp. 2729-2744.
  12. RAO, J. N. K., SUTRADHAR, B. C., YUE, K., (1993). Generalized Least Squares F Test in Regression Analysis with Two-Stage Cluster Samples. Journal of the American Statistical Association, 88 (424), pp. 1388-1391.
  13. RAO, J. N. K., WANG, S. G., (1995). On the Power of F Tests under Regression Models with Nested Error Structure. Journal of Multivariate Analysis, 53, pp. 237-246.
  14. SMITH, C. A. B., (1980). Estimating Genetic Correlations. Ann. Human Genetics, 43, pp. 265-284.
  15. SRIVASTAVA, M. S., KATAPA, R. S., (1986). Comparison of Estimators of Interclass and Intraclass Correlations from Familial Data. The Canadian Journal of Statistics, 14 (1), pp. 29-42.
  16. WU, C. F. J., HOLT, D., HOLMES, D. J., (1988). The Effect of Two-Stage Sampling on the F Statistic. Journal of the American Statistical Association, 83 (401), pp. 150-159.
Cytowane przez
Pokaż
ISSN
1234-7655
Język
eng
URI / DOI
http://dx.doi.org/10.21307/stattrans-2019-009
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