> > Alex Yu wrote:
> > >
> > > Disadvantages of non-parametric tests:
> > >
> > > Losing precision: Edgington (1995) asserted that when more precise
> > > measurements are available, it is unwise to degrade the precision by
> > > transforming the measurements into ranked data.

Edgington's comment is off the mark in most cases.  The efficiency of the
Wilcoxon-Mann-Whitney test is 3/pi (0.96) with respect to the t-test
IF THE DATA ARE NORMAL.  If they are non-normal, the relative
efficiency of the Wilcoxon test can be arbitrarily better than the t-test.
Likewise, Spearman's correlation test is quite efficient (I think the
efficiency is 9/pi^2) relative to the Pearson r test if the data are
bivariate normal.

Where you lose efficiency with nonparametric methods is with estimation
of absolute quantities, not with comparing groups or testing correlations.
The sample median has efficiency of only 2/pi against the sample mean
if the data are from a normal distribution.
Frank E Harrell Jr
Professor of Biostatistics and Statistics
Division of Biostatistics and Epidemiology
Department of Health Evaluation Sciences
University of Virginia School of Medicine

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