Nonparametric Estimation of Latent Treatment Effects for Two Armed Clinical Trials Using Infinite Mixture Models
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| Publicado en: | ProQuest Dissertations and Theses (2025) |
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ProQuest Dissertations & Theses
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| Acceso en línea: | Citation/Abstract Full Text - PDF |
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| Resumen: | Control versus treatment clinical trials are prone to averaging over individual effects to produce a one size fits all conclusion of whether a drug/procedure have efficacy, on average. However, it is often the case that subjects have their own unique response to treatment that are not necessarily captured by an average effect size. We have developed an infinite mixture model that can produce a nonparametric estimate of the latent distribution of treatment effects for a population. The estimated distribution of treatment effects enables researchers to make conclusions about what percentage of the population will have a treatment effect of a specified size (i.e. medically significant), without assuming a parametric form on their data. This development opens the door for personalized medicine to be statistically modeled in two arm clinical trials. |
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| ISBN: | 9798288852756 |
| Fuente: | ProQuest Dissertations & Theses Global |