Model Checking for Logistic Models with Study of Telehealth During the COVID-19 Pandemic Among PWH in DC

Zeyu Yang, Hua Liang (), Huiling Liu, Shannon Barth, Morgan Byrne, Elisabeth Andersen, Vinay Bhandaru and Amanda Castel
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Zeyu Yang: George Washington University (GWU)
Hua Liang: George Washington University (GWU)
Huiling Liu: South China University of Technology
Shannon Barth: GWU
Morgan Byrne: GWU
Elisabeth Andersen: GWU
Vinay Bhandaru: GWU
Amanda Castel: GWU

Statistics in Biosciences, 2025, vol. 17, issue 3, No 9, 774-789

Abstract: Abstract We propose a projection-based test to check logistic regression models and apply the test to study telehealth utilization during the COVID-19 pandemic among patients with HIV. The test is shown to be consistent and can detect root-n local alternatives. The use of the proposed test to investigate a COVID-19 dataset reveals that the probability of telehealth utilization depends on the following variables: overweight, education, and age and the interaction between age and ethnicity. Specifically, the probability for the Hispanic group decreases with older age, whereas there is no trend between the probability with the age for the group of non-Hispanic. This interaction may be ignored when we apply other goodness-of-fit methods. The simulation studies also show the performance of the proposed method is remarkably attractive compared to its competitors.

Keywords: Consistent test; COVID-19; Goodness-of-fit; Logistic regression; Person living with HIV (PWH); Projection; Telehealth (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s12561-024-09457-2

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