We introduce a new approach to regression with imprecisely observed data, combining likelihood inference with ideas from imprecise probability theory, and thereby taking different kinds of uncertainty into account. The approach is very general : it provides a uniform theoretical framework for regression analysis with imprecise data, where all kinds of relationships between the variables of interest may be considered and all types of imprecisely observed data are allowed.