DOAJ Open Access 2024

Covariate adjusted nonparametric methods under propensity analysis

Jiabu Ye Dejian Lai

Abstrak

Propensity score is one of the most commonly used score functions in adjusting for covariates effect in statistical inference. It is important to understand the impact with propensity score in case some of the prespecified covariates are severely imbalanced. In this article, we performed simulation evaluation the empirical type 1 error and empirical power under scenario of imbalanced covariates in several nonparametric two sample tests with propensity score or with other covariate adjustments. Our results suggest common propensity score approaches might have type 1 error inflation at scenarios with severe imbalanced covariates or model is mis-specified.

Topik & Kata Kunci

Applied mathematics. Quantitative methods Probabilities. Mathematical statistics

Penulis (2)

Jiabu Ye

Dejian Lai

Format Sitasi

APA MLA BibTeX

Ye, J., Lai, D. (2024). Covariate adjusted nonparametric methods under propensity analysis. https://doi.org/10.3389/fams.2024.1357816

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Informasi Jurnal

Tahun Terbit: 2024
Sumber Database: DOAJ
DOI: 10.3389/fams.2024.1357816
Akses: Open Access ✓