Identify the underlying true model from other models for clinical practice using model performance measures

The study found the true model is not always identified as the "outperformed" model by current conventional measures for binary outcome, even though such true model is presented in the clinical data. New statistical approaches or measures should be established to identify the casual true model from proxy models, especially for those in proxy models with extra noises and/or missing causal predictors.

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Publication Details

Journal
BMC Medical Research Methodology
Published
2025-01-09
DOI
https://doi.org/10.1186/s12874-025-02457-w
Primary Topic
Statistical Methods in Clinical Trials
Type
article
Field-Weighted Citation Impact
0.00

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article

Identify the underlying true model from other models for clinical practice using model performance measures

Yan Li
BMC Medical Research Methodology
Statistical Methods in Clinical Trials
article

Identify the underlying true model from other models for clinical practice using model performance measures

Yan Li
article en

Abstract

The study found the true model is not always identified as the "outperformed" model by current conventional measures for binary outcome, even though such true model is presented in the clinical data. New statistical approaches or measures should be established to identify the casual true model from proxy models, especially for those in proxy models with extra noises and/or missing causal predictors.

BMC Medical Research MethodologyVol. 25(1)
Xiamen University (CN)
Xiamen University
Openalex Percentile: Top 99%
Statistical Methods in Clinical Trials
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