A Cell Transformation Assay (CTA) is an in-vitro method to test a chemical for carcinogenicity. In a recent contribution from an international expert group created to improve the analysis in BALB/c 3T3 CTA data, two classes of models in the frequentist paradigm were recommended. Here a Bayesian model for potential outcomes is developed to estimate the causal effect of some concentrations of a candidate carcinogen on counts of foci growing within Petri dishes. The reanalysis of an actual case study is performed to illustrate some limitations of current models and the main features of the proposed approach.

Causal analysis of Cell Transformation Assays / Stefanini, Federico Mattia. - ELETTRONICO. - (2017), pp. 949-954. (Intervento presentato al convegno SIS 2017: STATISTICS AND DATA SCIENCE: NEW CHALLENGES, NEW GENERATIONS tenutosi a Florence nel 28-30 July 2017) [10.36253/978-88-6453-521-0].

Causal analysis of Cell Transformation Assays

STEFANINI, FEDERICO MATTIA
2017

Abstract

A Cell Transformation Assay (CTA) is an in-vitro method to test a chemical for carcinogenicity. In a recent contribution from an international expert group created to improve the analysis in BALB/c 3T3 CTA data, two classes of models in the frequentist paradigm were recommended. Here a Bayesian model for potential outcomes is developed to estimate the causal effect of some concentrations of a candidate carcinogen on counts of foci growing within Petri dishes. The reanalysis of an actual case study is performed to illustrate some limitations of current models and the main features of the proposed approach.
2017
SIS2917: STATISTICS AND DATA SCIENCE: NEW CHALLENGES, NEW GENERATIONS
SIS 2017: STATISTICS AND DATA SCIENCE: NEW CHALLENGES, NEW GENERATIONS
Florence
28-30 July 2017
Stefanini, Federico Mattia
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1089529
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