Abstract
The aim of this book is to provide the reader with an interesting selection of papers on modern statistical model development in bio-statistics and bio-informatics. The book also attempts to celebrate, in passing, the work of John Nelder who made an enormous contribution to statistical model development. The papers presented herein have been compiled from several sources. The majority contribution by numbers stems from Science Foundation Ireland’s BIO-SI project (www3.ul.ie/bio-si) centred in the Universities of Limerick and Galway in Ireland. However, the volume has also been exceptionally fortunate to attract papers from several distinguished international statisticians who had participated in a Workshop on Correlated Data Modelling held in the University of Limerick (www3.ul..ie/wcdm07). The various papers offered represent a refreshing blend of experience and youth as the next generation of researchers begin to contribute.
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References
Lee, Y., Nelder, J. A., & Pawitan, Y. (2006). Generalised linear models with random effects: Unified analysis via h-likelihood. London: Chapman and Hall.
MacKenzie, G. (1996). Regression models for survival data: The generalised time dependent logistic family. Journal of the Royal Statistical Society, 45, 21–34.
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© 2014 Springer International Publishing Switzerland
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MacKenzie, G., Peng, D. (2014). Introduction. In: MacKenzie, G., Peng, D. (eds) Statistical Modelling in Biostatistics and Bioinformatics. Contributions to Statistics. Springer, Cham. https://doi.org/10.1007/978-3-319-04579-5_1
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DOI: https://doi.org/10.1007/978-3-319-04579-5_1
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