Decision-Making in Sequential Adaptive Clinical Trials, with Implications for Drug Misclassification and Resource Allocation

2019 ◽  
pp. 321-345
Author(s):  
Alba C. Rojas-Cordova ◽  
Ebru K. Bish ◽  
Niyousha Hosseinichimeh
Keyword(s):  
Decision Making ◽  
Resource Allocation ◽  
Clinical Trials ◽  
Adaptive Clinical Trials

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

2021 ◽  
Author(s):  
Alessandro Baldi Antognini ◽  
Marco Novelli ◽  
Maroussa Zagoraiou
Keyword(s):  
Clinical Trials ◽  
Primary Outcome ◽  
Wald Test ◽  
Simple Solution ◽  
Nuisance Parameters ◽  
Simulation Studies ◽  
Fundamental Properties ◽  
Adaptive Clinical Trials ◽  
Treatment Comparisons ◽  
Practical Recommendations

AbstractThe present paper discusses drawbacks and limitations of likelihood-based inference in sequential clinical trials for treatment comparisons managed via Response-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.

Employing needs-based funding formulae – some unavoidable tradeoffs

2017 ◽  
Vol 31 (7) ◽  
pp. 1092-1102
Author(s):  
Tal Gilead ◽  
Iris BenDavid-Hadar
Keyword(s):  
Decision Making ◽  
Resource Allocation ◽  
Design Methodology ◽  
Social Equity ◽  
School Resources ◽  
Content Type ◽  
Funding Formula ◽  
Policy Goals ◽  
Theoretical Investigations ◽  
Schooling System

Purpose The method by which the state allocates resources to its schooling system can serve as an important instrument for achieving desired improvements in levels of educational attainment, social equity and other social policy goals. In many school systems, the allocation of school resources is done according to a needs-based funding formula. The purpose of this paper is to provide a deeper understanding of some significant tradeoffs involved in employing needs-based funding formulae. Design/methodology/approach The paper is based on theoretical investigations of normative aspects involved in using needs-based funding formulae. Findings There are a number of underexplored complications and difficulties that arise from the use of needs-based funding formulae. Dealing with these involves significant tradeoffs that require taking normative decisions. Understanding these tradeoffs is important for improving the use of needs-based funding formulae. Originality/value The paper highlights three under-examined issues that emerge from the current use of needs-based funding formulae. These issues are: to what extent funding formulae should be responsive to social and economic needs? To what extent should funding formulae allow for the use of discretion in resource allocation? To what degree needs-based formulae funding should be linked to outcomes? By discussing these issues and the tradeoffs involved in them, the paper provides a deeper understanding of significant aspects stemming from the use of needs-based funding formulae. This, in turn, can serve as a basis for an improved and better informed process for decision making regarding the use of funding formulae.

scholarly journals Critical concepts in adaptive clinical trials

2018 ◽  
Vol Volume 10 ◽  
pp. 343-351 ◽  
Author(s):  
Jay JH Park ◽  
Kristian Thorlund ◽  
Edward J Mills
Keyword(s):  
Clinical Trials ◽  
Adaptive Clinical Trials

A Statistical Framework for Decision Making in Confirmatory Multipopulation Tailoring Clinical Trials

2012 ◽  
Vol 46 (6) ◽  
pp. 647-656 ◽  
Author(s):  
Brian A. Millen ◽  
Alex Dmitrienko ◽  
Stephen Ruberg ◽  
Lei Shen
Keyword(s):  
Decision Making ◽  
Clinical Trials ◽  
Statistical Framework
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