This text introduces a general framework for sensitivity analysis in multi-objective decision making. It deals with decision making under partial information. The proper axiomatic foundations are developed, a convenient paramentric model is introduced and the adequate solution concepts are analyzed, together with algorithms to compute them. A theory of decision making, new sensitivity tools based on gauge functions and Bayesian hypothesis testing, and a description of their implementation are included.