Search

Your search keyword '"De Santis, Fulvio"' showing total 73 results
Start Over Author "De Santis, Fulvio"
73 results on '"De Santis, Fulvio"'

58. Mixtures of prior distributions for predictive Bayesian sample size calculations in clinical trials

Author

Brutti, Pierpaolo, DE SANTIS, Fulvio, and Gubbiotti, Stefania

Subjects
Selective Estrogen Receptor Modulators, Clinical Trials as Topic, Likelihood Functions, Biometry, Models, Statistical, analysis prior, Myocardial Infarction, Bayes Theorem, Breast Neoplasms, sample size re-estimation, Magnesium Sulfate, Tamoxifen, Clinical Trials, Phase II as Topic, design prior, Clinical Trials, Phase III as Topic, phase ii and phase iii clinical trials, sample size determination, Sample Size, Odds Ratio, Humans, Female, Neoplasm Recurrence, Local, Monte Carlo Method, Randomized Controlled Trials as Topic
Abstract

In this paper we propose a predictive Bayesian approach to sample size determination (SSD) and re-estimation in clinical trials, in the presence of multiple sources of prior information. The method we suggest is based on the use of mixtures of prior distributions for the unknown quantity of interest, typically a treatment effect or an effects-difference. Methodologies are developed using normal models with mixtures of conjugate priors. In particular we extend the SSD analysis of Gajewski and Mayo (Statist. Med. 2006; 25:2554-2566) and the sample size re-estimation technique of Wang (Biometrical J. 2006; 48(5):1-13).

Published
2009

72. Multiple Testing Procedures Under Dependence, With Applications

Author

Farcomeni, Alessio and De Santis, Fulvio

Subjects
Settori Disciplinari MIUR::Scienze economiche e statistiche::STATISTICA, Multiple Comparisons, Scienze economiche e statistiche::STATISTICA [Settori Disciplinari MIUR], Hypothesis Testing, Dependence, DNA Microarrays, False Discovery Rate
Abstract

Domenico Marinucci, Enzo Orsingher, Silvia Terzi

Published
2005

73. Accounting for historical information in designing experiments: the Bayesian approach.

Author

De Santis F and Perone Pacifico M

Subjects
Binomial Distribution, Bayes Theorem, Research Design statistics & numerical data
Abstract

Two of the most important statistical problems in human and animal experimentation are the selection of an appropriate number of units to include in a given study and the allocation of these units to the various treatments. Properly addressing these issues allows the units to be used as efficiently as possible, which can contribute to addressing the overall issue of reducing the number of subjects in experimentation. To do so, reliable historical information is of particular importance. In the present paper, we describe the Bayesian approach to determining sample size and allocating units, with particular regard to how the use of historical data can be optimised. The paper focuses on two specific problems: the comparison of normal means and of binomial proportions.

Published
2004

Catalog

Books, media, physical & digital resources
See catalog results