Blog Archives

Beware the Friedman test!

February 14, 2012
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Beware the Friedman test!

In section 10.4.4 of Serious stats (Baguley, 2012) I discuss the rank transformation and suggest that it often makes sense to rank transform data prior to application of conventional ‘parametric’ least squares procedures such as t tests or one-way ANOVA. There are several advantages to this approach over the usual approach (which involves learning and applying a new test such as Mann-Whitney U,

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Comparing correlations: independent and dependent (overlapping or non-overlapping)

February 5, 2012
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Comparing correlations: independent and dependent (overlapping or non-overlapping)

In Chapter 6 (correlation and covariance) I consider how to construct a confidence interval (CI) for the difference between two independent correlations.  The standard approach uses the Fisher z transformation to deal with boundary effects (the squashing of the distribution and increasing asymmetry as r approaches -1 or 1). As zr is approximately normally distributed

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