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

ISBN-10: 0817643680

ISBN-13: 9780817643683

ISBN-10: 081764542X

ISBN-13: 9780817645427

Statistical equipment became more and more very important and now shape essential a part of learn within the future health sciences. Many subtle methodologies were built for particular purposes and difficulties. This self-contained quantity, an outgrowth of an "International convention on Statistical tools in healthiness Sciences," covers a variety of themes relating new statistical tools and novel functions within the wellbeing and fitness sciences.

The chapters, written by way of best specialists of their respective fields, are thematically divided into the next areas:

* Prognostic reviews and common epidemiology

* Pharmacovigilance

* caliber of life

* Survival analysis

* Clustering

* security and efficacy assessment

* medical design

* versions for the environment

* Genomic analysis

* Animal health

This finished quantity could be hugely invaluable an of significant curiosity to the wellbeing and fitness technology neighborhood in addition to practitioners, researchers, and graduate scholars in utilized likelihood, records, and biostatistics.

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Read Online or Download Advances in Statistical Methods for the Health Sciences: Applications to Cancer and AIDS Studies, Genome Sequence Analysis, and Survival Analysis PDF

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

Example text

The natural first step is to carry out a careful search of electronic databases for relevant studies. It is advisable not to rely only on PubMed; other databases may be fruitful. Strategies for searching for prognostic studies have been described by McKibbon et al. (1995). However, in the present context, searching needs to be more comprehensive than just searching for published results as the aim here is to identify groups who might have relevant data. Thus, for example, it would be useful also to identify published studies of the comparison of assays or methods of measuring the marker of interest in patients with the disease of interest.

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). Reporting recommendations for tumor marker prognostic studies (REMARK), Journal of the National Cancer Institute, 97, 1180–1184.

Volm, German Cancer Research Center, Heidelberg, Germany; and Y. Yamazaki, Hokkaido University School of Medicine, Kitaku, Sapporo, Japan. 16 D. G. Altman et al. References 1. Altman, D. G. (2001). Systematic reviews of evaluations of prognostic variables, British Medical Journal, 323, 224–228. 2. Altman, D. , and Schumacher, M. (1994). Dangers of using “optimal” cutpoints in the evaluation of prognostic factors, Journal of the National Cancer Institute, 86, 829–835. 3. Altman, D. , and Lyman, G.

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Advances in Statistical Methods for the Health Sciences: Applications to Cancer and AIDS Studies, Genome Sequence Analysis, and Survival Analysis by Douglas G. Altman, Marialena Trivella, Francesco Pezzella, Adrian L. Harris (auth.), Jean-Louis Auget, N. Balakrishnan, Mounir Mesbah, Geert Molenberghs (eds.)


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