By Douglas G. Altman, Marialena Trivella, Francesco Pezzella, Adrian L. Harris (auth.), Jean-Louis Auget, N. Balakrishnan, Mounir Mesbah, Geert Molenberghs (eds.)

Statistical tools became more and more vital and now shape crucial a part of study within the overall healthiness sciences. Many subtle methodologies were constructed for particular functions and difficulties. This self-contained quantity, an outgrowth of an "International convention on Statistical equipment in future health Sciences," covers quite a lot of subject matters relating new statistical equipment and novel functions within the future health sciences.

The chapters, written through major specialists of their respective fields, are thematically divided into the next areas:

* Prognostic reports and normal epidemiology

* Pharmacovigilance

* caliber of life

* Survival analysis

* Clustering

* defense and efficacy assessment

* scientific design

* versions for the environment

* Genomic analysis

* Animal health

This complete quantity may be hugely precious an of serious curiosity to the future health technology group in addition to practitioners, researchers, and graduate scholars in utilized chance, records, and biostatistics.

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Additional info for Advances in Statistical Methods for the Health Sciences: Applications to Cancer and AIDS Studies, Genome Sequence Analysis, and Survival Analysis

Sample text

Beex, L. , Klijn, J. , and Foekens, J. A. (2002). Pooled analysis of prognostic impact of urokinasetype plasminogen activator and its inhibitor PAI-1 in 8377 breast cancer patients, Journal of the National Cancer Institute, 94, 116–128. 13. McKibbon, K. , and Wilczynski, N. (1995). Beyond ACP Journal Club: How to harness MEDLINE for prognosis problems, ACP Journal Club, 123. A12–A14. 14. McShane, L. , Altman, D. , Taube, S. , Clark, G. M. for the Statistics Subcommittee of the NCI/EORTC Working Group on Cancer Diagnostics (2005).

25. , Brancati, F. , Powe, N. , and Golden, S. H. (2004). Meta-analysis: Glycosylated hemoglobin and cardiovascular disease in diabetes mellitus, Annals of Internal Medicine, 141, 421–431. 26. Simon, R. (2001). , M. K. Gospodarowicz, D. E. Henson, R. V. P. Hutter, B. O’Sullivan, L. H. Sobin, and C. Wittekind), pp. 49–56, Wiley-Liss, New York. 27. , and Altman, D. G. (1994). Statistical aspects of prognostic factor studies in oncology, British Journal of Cancer, 69, 979–985. 28. Stewart, L. , and Clarke, M.

And Clarke, M. J. (1995). Practical methodology of metaanalyses (overviews) using updated individual patient data. Cochrane Working Group, Statistics in Medicine, 14, 2057–2079. 29. Trivella, M. , Altman, D. , and Harris, A. L. (2006). Angiogenesis as a prognostic factor in non-small cell lung carcinoma. A meta-analysis using individual patient data, Submitted for publication. 30. Williamson, P. , Smith, C. , Hutton, J. , and Marson, A. G. (2002). Aggregate data meta-analysis with time-to-event outcomes, Statistics in Medicine, 21, 3337–3351.

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