Machine learning analysis plans for randomised controlled trials: detecting treatment effect heterogeneity with strict control of type I error.
Background: Retrospective exploratory analyses of randomised controlled trials (RCTs) seeking to identify treatment effect heterogeneity (TEH) are prone to bias and false positives. Yet the desire to learn all we can from exhaustive data measurements on trial participants motivates the inclusion of...
| Publicado en: | Trials Vol. 21; no. 1; pp. 1 - 11 |
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| Autores principales: | , |
| Formato: | equations & formulas research tables/charts Journal Article |
| Publicado: |
BioMed Central
2/10/2020
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| Acceso en línea: | Ver este registro en EBSCOhost |