In this paper we consider the estimation of probabilistic
ranking models in the context of conjoint experiments. By using
approximate rather than exact ranking probabilities, we do not
need to compute high-dimensional integrals. We extend the
approximation technique proposed by \\citet{Henery1981} in the
Thurstone-Mosteller-Daniels model for any Thurstone order
statistics model and we show that our approach allows for a
unified approach. Moreover, our approach also allows for the
analysis of any partial ranking. Partial rankings are essential
in practical conjoint analysis to collect data efficiently to
relieve respondents' task burden
