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This book focuses on the comparison, contrast, and assessment of risks on the basis of clinical investigations. It develops basic concepts as well as deriving 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 random effects models. The text then moves on to present a more modern likelihood- or model-based approach, which includes unconditional and conditional logistic regression; the analysis of count data and the Poisson regression model; the analysis of event time data, including the proportional hazards and multiplicative intensity models; and elements of categorical data analysis (expanded in this edition). SAS subroutines are both showcased in the text and embellished online by way of a dedicated author website. The book contains a technical, but accessible appendix that presents the core mathematical statistical theory used for the development of classical and modern statistical methods
This book investigates the comparison, contrast, and assessment of risks within clinical investigations by developing biostatistical methods. It derives these methods through both classical mathematical statistical tools and modern likelihood-based theories, presenting a comprehensive approach to analyzing data from clinical studies.
The book is structured to provide a technical yet accessible exploration of biostatistical methods, suitable for those needing to understand risk assessment in clinical investigations. Its approach balances classical statistical tools with modern likelihood-based theories, suggesting a comprehensive resource for researchers and statisticians. The inclusion of SAS subroutines and a detailed mathematical appendix indicates a focus on practical application and theoretical grounding. The content covers a wide range of analytical techniques, from basic table analysis to advanced regression models for various data types.
Page Count:
622
Publication Date:
2011-01-01
ISBN-10:
0470508221
ISBN-13:
9780470508220
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