Robust conditional inference for location parameters.

The robustness properties of conditional normal-theory procedures of inference for a location parameter are considered; in particular, a robust conditional density is proposed to be used instead of the classical methods based on the assumption of normality. The new density is conditional on a robust ancillary and its properties are studied in comparison to the exact conditional density but also under slight violations of the normal model assumption.