A new goodness-of-fit measure for probit models: Surrogate R².

ABSTRACT: Probit models are used extensively for inferential purposes in the social sciences as discrete data are prevalent in a vast body of social studies. Among many accompanying model inference problems, a critical question remains unsettled: how to develop a goodness-of-fit measure that resembles the ordinary least square (OLS) R² used for linear models. Such a measure has long been sought to achieve 'comparability' of different empirical models across multiple samples addressing similar social questions. To this end, we propose a novel R² measure for probit models using the notion of surrogacy - simulating a continuous variable S as a surrogate of the original discrete response (Liu & Zhang, Journal of the American Statistical Association, 113, 845 and 2018). The proposed

SUBMITTER: Liu D 

PROVIDER: S-EPMC10092347 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature