The Assessment of Relative RiskseBook - 2011
". . . an excellent textbook . . . an indispensable referencefor biostatisticians and epidemiologists."
-- International Statistical Institute
A new edition of the definitive guide to classical and modernmethods of biostatistics
Biostatistics consists of various quantitative techniques thatare essential to the description and evaluation of relationshipsamong biologic and medical phenomena. Biostatistical Methods:The Assessment of Relative Risks, Second Edition develops basicconcepts and derives an expanded array of biostatistical methodsthrough the application of both classical statistical tools andmore modern likelihood-based theories. With its fluid and balancedpresentation, the book guides readers through the importantstatistical methods for the assessment of absolute and relativerisks in epidemiologic studies and clinical trials withcategorical, count, and event-time data.
Presenting a broad scope of coverage and the latest research onthe topic, the author begins with categorical data analysis methodsfor cross-sectional, prospective, and retrospective studies ofbinary, polychotomous, and ordinal data. Subsequent chapterspresent modern model-based approaches that include unconditionaland conditional logistic regression; Poisson and negative binomialmodels for count data; and the analysis of event-time dataincluding the Cox proportional hazards model and itsgeneralizations. The book now includes an introduction to mixedmodels with fixed and random effects as well as expanded methodsfor evaluation of sample size and power. Additional new topicsfeatured in this Second Edition include:Establishing equivalence and non-inferiority Methods for the analysis of polychotomous and ordinal data,including matched data and the Kappa agreement index Multinomial logistic for polychotomous data and proportionalodds models for ordinal data Negative binomial models for count data as an alternative tothe Poisson model GEE models for the analysis of longitudinal repeated measuresand multivariate observations
Throughout the book, SAS is utilized to illustrate applicationsto numerous real-world examples and case studies. A related websitefeatures all the data used in examples and problem sets along withthe author's SAS routines.
Biostatistical Methods, Second Edition is an excellentbook for biostatistics courses at the graduate level. It is also aninvaluable reference for biostatisticians, applied statisticians,and epidemiologists.