Biostatistics and Statistical Inference for Health Research

Biostatistics and Statistical Inference for Health Research provides a systematic account of the statistical principles and methods used to analyse variation, quantify uncertainty and interpret empirical evidence in health research.The volume begins with probability theory and develops frequentist and Bayesian approaches to statistical inference before turning to linear and generalized models, multivariable and hierarchical modelling, and time-to-event analysis. Further chapters address missing data and measurement error, survey sampling and complex designs, model diagnostics and validation, prediction and calibration, longitudinal and time-series methods, and the principles of transparent statistical reporting and reproducible analysis.Particular attention is given to the relationship between a statistical result and the scientific question it is intended to address. Estimates, intervals, model coefficients and predictive measures are therefore considered in relation to the target population, study design, measurement process, modelling assumptions, dependence structure and sources of uncertainty.The book is intended as an educational and methodological reference for graduate and postgraduate students, researchers, epidemiologists, public-health professionals and other readers who require a rigorous foundation in biostatistical analysis and statistical inference for health research.