Monte Carlo methods were employed to investigate the effect of nonnormality on the bias associated with the squared canonical correlation coefficient (Rc2). The majority of Rc2 estimates were found to be extremely biased, but the magnitude of bias was impacted little by the degree of nonnormality
Non-zero correlation coefficients have non-normal distributions, affecting both means and standard d...
Variants of Cohen’s d, in this instance dt and dadj, has the largest influence on U1 measures used w...
Monte Carlo approach was employed to investigate the accuracy of Bobko's (1983) formulas for the bia...
Monte Carlo methods were employed to investigate the effect of nonnormality on the bias associated w...
This study examined bias in the sample correlation coefficient, r, and its correction by unbiased es...
This study examined bias in the sample correlation coefficient, r, and its correction by unbiased es...
The importance of structure coefficients and analogs of regression weights for analysis within the g...
Canonical correlation analysis is a powerful statistical method subsuming other parametric significa...
As restricted canonical correlation with a nonnegativity condition on the coefficients depend only o...
As restricted canonical correlation with a nonnegativity condition on the coefficients depend only o...
Scale coarseness is a pervasive yet ignored methodological artifact that attenuates observed correla...
Scale coarseness is a pervasive yet ignored methodological artifact that attenuates observed correla...
Scale coarseness is a pervasive yet ignored methodological artifact that attenuates observed correla...
This is Part 3 of a tutorial series on the nonadditivity of correlation coefficients. The bias natur...
In this article, a nonparametric correlation coefficient is defined that is based on the principle o...
Non-zero correlation coefficients have non-normal distributions, affecting both means and standard d...
Variants of Cohen’s d, in this instance dt and dadj, has the largest influence on U1 measures used w...
Monte Carlo approach was employed to investigate the accuracy of Bobko's (1983) formulas for the bia...
Monte Carlo methods were employed to investigate the effect of nonnormality on the bias associated w...
This study examined bias in the sample correlation coefficient, r, and its correction by unbiased es...
This study examined bias in the sample correlation coefficient, r, and its correction by unbiased es...
The importance of structure coefficients and analogs of regression weights for analysis within the g...
Canonical correlation analysis is a powerful statistical method subsuming other parametric significa...
As restricted canonical correlation with a nonnegativity condition on the coefficients depend only o...
As restricted canonical correlation with a nonnegativity condition on the coefficients depend only o...
Scale coarseness is a pervasive yet ignored methodological artifact that attenuates observed correla...
Scale coarseness is a pervasive yet ignored methodological artifact that attenuates observed correla...
Scale coarseness is a pervasive yet ignored methodological artifact that attenuates observed correla...
This is Part 3 of a tutorial series on the nonadditivity of correlation coefficients. The bias natur...
In this article, a nonparametric correlation coefficient is defined that is based on the principle o...
Non-zero correlation coefficients have non-normal distributions, affecting both means and standard d...
Variants of Cohen’s d, in this instance dt and dadj, has the largest influence on U1 measures used w...
Monte Carlo approach was employed to investigate the accuracy of Bobko's (1983) formulas for the bia...