Premium
Harmonic Mean Approach to Regression Analysis Under Heteroscedasticity and Nonnormality
Author(s) -
Tabatabai M. A.,
Tan W. Y.
Publication year - 1986
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/bimj.4710280707
Subject(s) - heteroscedasticity , mathematics , statistics , monte carlo method , normality , econometrics , sample size determination
In this paper, by combining the harmonic mean approach with the Welch and the James procedure (see WELCH 1951, JAMES, 1951), we develop some robust procedures for testing parallelism in several straight lines under heteroscedasticity and nonnormality. Through Monte Carlo simulations it is shown that these new tests are quite robust with respect to departure from normality. For small sample sizes, however, the TAN‐TABATABAI (1984) F β and F * β tests appear to be more powerful than the new tests, although when sample sizes are not small, there are hardly any differences between the Tan‐Tabatabai F β and F * β tests and the new tests.