The present paper discusses drawbacks and limitations of likelihood-based inference in sequential clinical trials for treatment comparisons managed viaResponse-Adaptive Randomization. Taking into account the most common statistical models for the primary outcome—namely binary, Poisson, exponential and normal data—we derive the conditions under which (i) the classical confidence intervals degenerate and (ii) the Wald test becomes inconsistent and strongly affected by the nuisance parameters, also displaying a non monotonic power. To overcome these drawbacks, we provide a very simple solution that could preserve the fundamental properties of likelihood-based inference. Several illustrative examples and simulation studies are presented in order to confirm the relevance of our results and provide some practical recommendations.

Baldi Antognini, A., Novelli, M., Zagoraiou, M. (2022). A simple solution to the inadequacy of asymptotic likelihood-based inference for response-adaptive clinical trials. STATISTICAL PAPERS, 63, 157-180 [10.1007/s00362-021-01234-3].

A simple solution to the inadequacy of asymptotic likelihood-based inference for response-adaptive clinical trials

Baldi Antognini, Alessandro
;
Novelli, Marco;Zagoraiou, Maroussa
2022

Abstract

The present paper discusses drawbacks and limitations of likelihood-based inference in sequential clinical trials for treatment comparisons managed viaResponse-Adaptive Randomization. Taking into account the most common statistical models for the primary outcome—namely binary, Poisson, exponential and normal data—we derive the conditions under which (i) the classical confidence intervals degenerate and (ii) the Wald test becomes inconsistent and strongly affected by the nuisance parameters, also displaying a non monotonic power. To overcome these drawbacks, we provide a very simple solution that could preserve the fundamental properties of likelihood-based inference. Several illustrative examples and simulation studies are presented in order to confirm the relevance of our results and provide some practical recommendations.
2022
Baldi Antognini, A., Novelli, M., Zagoraiou, M. (2022). A simple solution to the inadequacy of asymptotic likelihood-based inference for response-adaptive clinical trials. STATISTICAL PAPERS, 63, 157-180 [10.1007/s00362-021-01234-3].
Baldi Antognini, Alessandro; Novelli, Marco; Zagoraiou, Maroussa
File in questo prodotto:
File Dimensione Formato  
11585_818946.pdf

accesso aperto

Tipo: Versione (PDF) editoriale
Licenza: Licenza per Accesso Aperto. Creative Commons Attribuzione (CCBY)
Dimensione 780.84 kB
Formato Adobe PDF
780.84 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/818946
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? 1
social impact