Predictive tests can produce either a binary classification of each individual as high or low risk, or a quantitative risk score that represents the degree of risk for each individual. Optimally, such a risk score is equal to the posterior probability of developing the disease (e.g. from logistic regression), although some widely used scores (such as risk allele counting) do not meet this criterion. Scores can be transformed into binary outcomes by defining high risk to be individuals with a score greater than a threshold T, and all others as low risk. Analysis of risk for quantitative traits is even more straightforward, as such transformations are unnecessary, and much of the discussion below is equally applicable to such non-categorical scenarios.
