Random Measures, ANOVA Models and Quantifying Uncertainty in Randomized Controlled Trials
Fuente:
arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2023
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| _version_ | 1866911215456878592 |
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| author | Bastian, Caleb Deen Rabitz, Herschel Rempala, Grzegorz A |
| author_facet | Bastian, Caleb Deen Rabitz, Herschel Rempala, Grzegorz A |
| contents | The paper introduces a novel approach to global sensitivity analysis, grounded in the variance-covariance structure of random variables derived from random measures. The proposed methodology facilitates the application of information-theoretic rules for uncertainty quantification, offering several advantages. Specifically, the approach provides valuable insights into the decomposition of variance within discrete subspaces, similar to the standard ANOVA analysis. To illustrate this point, the method is applied to datasets obtained from the analysis of randomized controlled trials on evaluating the efficacy of the COVID-19 vaccine and assessing clinical endpoints in a lung cancer study. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2312_10541 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Random Measures, ANOVA Models and Quantifying Uncertainty in Randomized Controlled Trials Bastian, Caleb Deen Rabitz, Herschel Rempala, Grzegorz A Methodology Quantitative Methods 92-05, 92-11 The paper introduces a novel approach to global sensitivity analysis, grounded in the variance-covariance structure of random variables derived from random measures. The proposed methodology facilitates the application of information-theoretic rules for uncertainty quantification, offering several advantages. Specifically, the approach provides valuable insights into the decomposition of variance within discrete subspaces, similar to the standard ANOVA analysis. To illustrate this point, the method is applied to datasets obtained from the analysis of randomized controlled trials on evaluating the efficacy of the COVID-19 vaccine and assessing clinical endpoints in a lung cancer study. |
| title | Random Measures, ANOVA Models and Quantifying Uncertainty in Randomized Controlled Trials |
| topic | Methodology Quantitative Methods 92-05, 92-11 |
| url | https://arxiv.org/abs/2312.10541 |