A robust score test of homogeneity for zero-inflated count data.

ABSTRACT: In many applications of zero-inflated models, score tests are often used to evaluate whether the population heterogeneity as implied by these models is consistent with the data. The most frequently cited justification for using score tests is that they only require estimation under the null hypothesis. Because this estimation involves specifying a plausible model consistent with the null hypothesis, the testing procedure could lead to unreliable inferences under model misspecification. In this paper, we propose a score test of homogeneity for zero-inflated models that is robust against certain model misspecifications. Due to the true model being unknown in practical settings, our proposal is developed under a general framework of mixture models for which a layer of randomness is imposed on

SUBMITTER: Hsu WW 

PROVIDER: S-EPMC9939047 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature