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Biostatistical methods the assessment of relative risks /

Comprehensive coverage of classical and modern methods of biostatistics. Biostatistical Methods focuses on the assessment of risks and relative risks on the basis of clinical investigations. It develops basic concepts and derives biostatistical methods through both the application of classical mathe...

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Bibliographic Details
Main Authors: Lachin, John M., 1942
Corporate Authors: Wiley InterScience Online service
Published:
Literature type: Electronic eBook
Language: English
Series: Wiley series in probability and statistics
Subjects:
Medical statistics
Health risk assessment > Statistical methods
Medicine > Research > Statistical methods
Statistiques médicales
Risques pour la santé > Évaluation
Médecine > Recherche > Méthodes statistiques
MEDICAL > Biostatistics
Statistische methoden
Geneeskunde
Biometry
Data Interpretation, Statistical
Models, Statistical
Risk Assessment > methods
Electronic books
Online Access: http://onlinelibrary.wiley.com/book/10.1002/9780470317051
Summary: Comprehensive coverage of classical and modern methods of biostatistics. Biostatistical Methods focuses on the assessment of risks and relative risks on the basis of clinical investigations. It develops basic concepts and derives biostatistical methods through both the application of classical mathematical statistical tools and more modern likelihood-based theories. The first half of the book presents methods for the analysis of single and multiple 2x2 tables for cross-sectional, prospective, and retrospective (case-control) sampling, with and without matching using fixed and two-stage rando
Carrier Form: 1 online resource (xvii, 529 pages).
Bibliography: Includes bibliographical references and indexes.
ISBN: 9780470317051
0470317051
9780470317891 (electronic bk.)
0470317892 (electronic bk.)
Index Number: RA409
CLC: Q-332
Contents: Biostatistical Methods The Assessment of Relative Risks; Contents; Preface; 1. Biostatistics and Biomedical Science; 2. Relative Risk Estimates and Tests for Two Independent Groups; 3. Sample Size, Power, and Efficiency; 4. Stratified-Adjusted Analysis for Two Independent Groups; 5. Case-Control and Matched Studies; 6. Applications of Maximum Likelihood and Efficient Scores; 7. Logistic Regression Models; 8. Analysis of Count Data; 9 Analysis of Event-Time Data; Appendix Statistical Theory; References; Author Index; Index.

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