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Re: st: Friedman tests
At 10:32 23/03/2005, Ronan Conroy wrote:
However, rank methods can be used to produce confidence intervals,
sometimes for median differences and/or median ratios on the scale of the
original outcome (so you do not lose the original measurement scale after
all). See, for instance, Newson (2002), which can be downloaded in preprint
form by typing
Ashley Harris wrote:
Data are not parametric or nonparametric. And, indeed, the terms are
confusing when applied to statistical procedures. I presume that you have
a dependent variable that you can't put into a regression or anova.
Nevertheless, before you head off an do a rank test, consider using some
of the more powerful alternatives.
What I have nonparametric data for 3 groups, 1 dependent variable (ratio)
and 2 independent variables (technique and analysis type).
- counted data: consider negative binomial regression (or Poisson, if
counts are of rare events)
- ordered categories: ordinal logistic regression springs to mind
With these techniques, you can explore multiple independent variables,
just as you can in regression. Of course, these models have assumptions,
just as any model does, and you should check that your data conform to
Rank tests tend to be an index of despair. They lose important information
by losing the original measurement scale of the dependent variable. This
allows you to assess statistical significance, but not real life importance.
Having said that, rank statistics are still subject to the limitations that
you cannot use them to calculate confounder-adjusted effects of an exposure
(except possibly by using propensity score methods, in which case you still
need regression statistics to define the propensity score). And Ronan is
entirely right to point out that there are no such things as "nonparametric
data", and that it is confusing and misleading even to talk about
"nonparametric statistical procedures".
I hope this helps.
Newson R. 2002. Parameters behind "nonparametric" statistics: Kendall's
tau, Somers' D and median differences. The Stata Journal 2(1): 45-64.
Lecturer in Medical Statistics
Department of Public Health Sciences
Division of Asthma, Allergy and Lung Biology
King's College London
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