In interval decision analysis, where input information is provided in terms of intervals or similar formats to represent imprecise input statements instead of using precise numbers for probabilities and consequence values, a vast array of techniques to conduct robustness and sensitivity analysis has emerged. At the same time, it is not straightforward how to relate these techniques to one another in a decision-analytic process and how they, in combination, serve as a source for obtaining insights into how imprecision affects decision evaluations. Therefore, this chapter aims to reflect upon a group of methods for robustness and sensitivity analyses that are compatible with a common framework for analysing decisions under risk, provide a systematic presentation of these, and discuss guidelines for their usage in decision analysis practice.