@inbook{9b70d33fd3e14a45aca89cfff682423e,
title = "Towards Argumentation for Statistical Model Selection",
abstract = "The increase in routine clinical data collection coupled with an expectation to exploit this in support of evidence based decision making creates the requirement for a system to support clinicians in this analysis. This paper looks at applying argumentation to this problem, by collating all the relevant statistical approaches and their assumptions into a statistical knowledge base and then representing the model selection process through argumentation. This will form the foundation for the development of a prototype that will enable clinicians to answer their research questions with no statistics, informatics or administrative support. ",
keywords = "Argumentation, Statistical Model Selection, Decision Support",
author = "Isabel Sassoon and Jeroen Keppens and Peter McBurney",
year = "2014",
doi = "10.3233/978-1-61499-436-7-67",
language = "English",
isbn = "978-1-61499-435-0",
series = "Frontiers in Artificial Intelligence and Applications",
publisher = "IOS Press",
pages = "61--74",
editor = "Simon Parsons and Nir Oren and Chris Reed and Federico Cerutti",
booktitle = "Fifth International Conference on Computational Models of Argument",
note = "Fifth International Conference on Computational Models of Argument ; Conference date: 09-09-2014 Through 12-09-2014",
}