Abstract
We revisit a hypothesis-testing problem recently investigated by de Leon and Carrière (2000). Specifically, we obtain exact likelihood ratio tests of one-sample location hypotheses for multivariate mixed data modeled according to the general location model (Olkin and Tate, 1961). The tests generalize those previously proposed by de Leon and Carrière (2000) for the case of mixed bivariate data. Optimal properties of the tests are briefly studied. Simulations show that the tests are reasonably powerful in detecting differences between the true and hypothesized populations. We illustrate the tests with a few examples, including one concerning data on academic achievement.
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