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An Appraisal of the Adjusted Association and the Relative EffectIssues with the Adjusted AssociationWhen both S and T are continuous normally distributed endpoints, there are no issues with the adjusted association (p_{Z}). Indeed, p_{Z} is simply the correlation between S and T adjusted for Z. This quantity has desirable properties, i.e., it always remains within the unit interval, it generally has a small confidence interval (because there is sufficient individuallevel replication in most clinical trials), and it is straightforward to compute and interpret. However, if we move away from the situation were both S and T are contin?uous normally distributed endpoints, it is no longer clear how p_{Z}, the adjusted association, should be quantified. For example, in the mixed continuousbinary setting, i.e., S is continuous and T is binary, a bivariate probit model can be used in which p_{Z} is defined as the correlation between a latent continuous variable that is assumed to underlie the observed discretized endpoint T and the continuous endpoint S. Alternatively, a bivariate PlackettDale model can be used in which p_{Z} is defined as the global odds ratio between S and T (Geys, 2005). A variety of other measures have been proposed to quantify p_{Z} in other settings (for details, see Burzykowski, Molenberghs, and Buyse, 2005). It would be desirable to have a single unifying approach to quantify p_{Z} across a wide variety of settings. In Chapter 10, an informationtheoretic approach is introduced for this purpose. 
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