In the analysis of ordered categorical data, the categories are often assigned a set of subjectively chosen order‐restricted scores. To overcome the arbitrariness involved in the assignment of the scores, several score‐independent tests have been proposed. However, these methods are limited to 2 × K contingency tables, where K is the number of ordered categories. We present an efficiency robust score‐independent test that is applicable to more general situations. The test is embedded into a flexible framework for conditional inference and provides a natural generalization of many familiar tests involving ordered categorical data, such as the generalized Cochran‐Mantel‐Haenszel test for singly or doubly ordered contingency tables, the Page test for randomized block designs and the Tarone‐Ware trend test for survival data. The proposed method is illustrated by several numerical examples.