a distribution, and reassigning their values to be identical to the next-highest or next-lowest value in the distribution. For example, subjects reporting AOS <8 (n=7) were assigned an AOS value of 8, those with AOS over 30 (n=13) were assigned a value of 30, and so on. This transformation is appropriate for variables that have approximately normal distribution, but exhibit kurtosis due to small numbers of outliers (Fernandez et al. 2002; Shete et al. 2004). We selected Winsoriation thresholds that reduced positive kurtosis without inducing negative kurtosis. This corresponded to highest and lowest 1–2% of the sample on each variable. Finally, all of these covariates were recoded so that the zero-value would reflect the sample median on the raw variable (AOS=16), and higher values would reflect risk, or earlier onset, rather than protection. We designate these recoded variables using a prefixed “r”. Hence, rAOS=16-AOS, after Winsorization.
