Abstract
In this chapter, we have used the chi-squared test and Yule’s Q measure to discover associations in tables of patient audiology data. These records are examples of heterogeneous medical records, since they contain audiograms, textual notes and typical relational fields. In our first experiment we used the chi-squared measure to discover associations between the different fields of audiology data such as patient gender and patient age with diagnosis and the type of hearing aid worn. Then, in our second experiment we used Yule’s Q to discover the strength and direction of the significant associations found by the chi-squared measure. Finally, we examined the likelihood ratio used in Bayesian evidence evaluation. We discuss our findings in the context of producing an audiology decision support system.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Pendharkar PC, Rodger JA, Yaverbaum GJ, Herman N, Benner M (1999) Association, statistical, mathematical and neural approaches for mining breast cancer patterns. Expert Syst Appl, Elsevier Science Ltd 17:223–232
Bramer M (2007) Principles of data mining. Springer, London, pp 187–218
Ordonez C, Ezquerra N, Santana CA (2006) Constraining and summarizing association rules in medical data. In: Cercone N et al (eds) Knowledge and information systems. Springer, New York, pp 259–283
Han J, Kamber M (2006) Data mining concepts and techniques, 2nd edn. Morgan Kaufmann Publishers, San Diego, pp 227–272
Altman DG (1991) Practical statistics for medical research. Chapman & Hall, London, pp 241–248, 211, 271
Lucy D (2005) Introduction to statistics for forensic scientists. Wiley, Chichester, pp 45–52,112–114,133–136
Oakes M, Gaizauskas R, Fowkes H et al (2001) Comparison between a method based on the chi-square test and a support vector machine for document classification. In: Proceedings of ACM SIGIR, New Orleans, pp 440–441
Chi-square calculator (2010). http://www.stat.tamu.edu/~west/applets/chisqdemo.html
Agresti A (2002) Categorical data analysis, 2nd ed. Wiley series in probability and statistics. Wiley, New York, p 80
Porter MF (1980) An algorithm for suffix stripping. Program 14(3):130–137
Anwar MN, Oakes MP, McGarry K (2010) Chi-squared and associations in tabular audiology data. In: Lecture notes in engineering and computer science: proceedings of the world congress on engineering 2010, WCE 2010, London, UK, vol 1, pp 346–351
Evett IW, Jackson G, Lambert JA, McCrossan S (2000) The impact of the principles of evidence interpretation and the structure and content of statements. Sci Justice 40:233–239
McGarry K (2005) A survey of interestingness measures for knowledge discovery. Knowl Eng Rev J 20(1):39–61
Acknowledgments
We wish to thank Maurice Hawthorne, Graham Clarke and Martin Sandford at the Ear, Nose and Throat Clinic at James Cook University Hospital in Middlesbrough, England, UK, for making the large set of audiology records available to us.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer Science+Business Media B.V.
About this chapter
Cite this chapter
Anwar, M.N., Oakes, M.P., McGarry, K. (2011). Chi-Squared, Yule’s Q and Likelihood Ratios in Tabular Audiology Data. In: Ao, SI., Gelman, L. (eds) Electrical Engineering and Applied Computing. Lecture Notes in Electrical Engineering, vol 90. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-1192-1_30
Download citation
DOI: https://doi.org/10.1007/978-94-007-1192-1_30
Published:
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-007-1191-4
Online ISBN: 978-94-007-1192-1
eBook Packages: EngineeringEngineering (R0)