A Monte Carlo Investigation of the Box-Cox Transformation in Small Samples

1978 ◽  
Vol 73 (363) ◽  
pp. 488 ◽  
Author(s):  
John J. Spitzer
Keyword(s):  
Monte Carlo ◽  
Small Samples ◽  
Monte Carlo Investigation ◽  
Box Cox Transformation

A Monte Carlo Investigation of the Fisher Z Transformation for Normal and Nonnormal Distributions

2000 ◽  
Vol 87 (3_suppl) ◽  
pp. 1101-1114 ◽  
Author(s):  
Kenneth J. Berry ◽  
Paul W. Mielke
Keyword(s):  
Monte Carlo ◽  
Correlation Coefficient ◽  
Bivariate Normal Distribution ◽  
Small Samples ◽  
Bivariate Distributions ◽  
Nonnormal Distributions ◽  
Monte Carlo Investigation ◽  
Sample Correlation ◽  
Heavy Tailed ◽  
Z Transformation

The Fisher transformation of the sample correlation coefficient r (1915, 1921) and two related techniques by Gayen (1951) and Jeyaratnam (1992) are examined for robustness to nonnormality. Monte Carlo analyses compare combinations of sample sizes and population parameters for seven bivariate distributions. The Fisher, Gayen, and Jeyaratnam approaches are shown to provide useful results for a bivariate normal distribution with any population correlation coefficient ρ and for nonnormal bivariate distributions when ρ = 0. In contrast, the techniques are virtually useless for nonnormal bivariate distributions when ρ#0.0. Surprisingly, small samples are found to provide better estimates than large samples for skewed and symmetric heavy-tailed bivariate distributions.

Faking and the Validity of Personality: A Monte Carlo Investigation

2005 ◽  
Author(s):  
Shawn Komar ◽  
Jennifer Theakston ◽  
Douglas J. Brown ◽  
Chet Robie
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Investigation
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