Thanks for your interest! The name of the area is "causal inference." Keywords: "standardization" (in epidemiology), "confounder or covariate adjustment," "propensity score", "instrumental variables", "back-door criterion," "front-door criterion," "g-formula", "potential outcomes", "ignorability," "inverse probability weighting," "mediation analysis," "interference", etc.

Pearl's Causality book (http://www.amazon.com/Causality-Reasoning-Inference-Judea-Pearl/dp/052189560X/ref=pd_sim_sbs_b_1) is a good overview (but doesn't talk a lot about statistics/estimation). Early references are Sewall Wright's path analysis paper from 1921 (http://naldc.nal.usda.gov/download/IND43966364/PDF) and Neyman's paper on potential outcomes from 1923 (http://www.ics.uci.edu/~sternh/courses/265/neyman_statsci1990.pdf). People say either Sewall Wright or his dad invented instrumental variables also.