Patent ID: 8688610

Claim:
A computer-implemented method comprising: receiving study data from a comparative study, wherein the study data are indicative of observed values of (i) exposure status, (ii) outcome, and (iii) one or more predictor variables, wherein each observed value is for a participant in the comparative study; calculating, for each respective participant in a set of participants in the study, a respective value of a causality variable, wherein the causality variable is a function of the observed values of exposure status and outcome for the respective participant, wherein an expectation of the causality variable for the respective participant is a monotone function of an individual causal effect (ICE) for the respective participant, and wherein the causality variable is a cadit variable defined as: cadit=TÃ—R+(1âˆ’T)Ã—(1âˆ’R), where T is exposure status defined as T=1 for a first treatment and T=0 for a second treatment and R is an outcome value; analyzing part of the study data to estimate a statistical relationship between the causality variable and the one or more predictor variables; and based at least in part on the estimated statistical relationship, generating an algorithm for distinguishing between individuals in accordance with values of the expectation of the causality variable for the individuals, wherein the algorithm uses values of the one or more predictor variables to distinguish between the individuals.