TY - BOOK ID - 4865151 TI - Innovative Statistical Methods for Public Health Data AU - Chen, Ding-Geng (Din). AU - Wilson, Jeffrey. PY - 2015 SN - 9783319185361 3319185357 9783319185354 3319185365 PB - Cham : Springer International Publishing : Imprint: Springer, DB - UniCat KW - Statistics. KW - Statistics for Life Sciences, Medicine, Health Sciences. KW - Public Health. KW - Laboratory Medicine. KW - Medical laboratories. KW - Public health. KW - Statistique KW - Santé publique KW - Mathematical Statistics KW - Mathematics KW - Physical Sciences & Mathematics KW - Public health KW - Statistical methods. KW - Community health KW - Health services KW - Hygiene, Public KW - Hygiene, Social KW - Public health services KW - Public hygiene KW - Sanitary affairs KW - Social hygiene KW - Laboratory medicine. KW - Health KW - Human services KW - Biosecurity KW - Health literacy KW - Medicine, Preventive KW - National health services KW - Sanitation KW - Diagnosis, Laboratory KW - Health facilities KW - Laboratories KW - Statistical analysis KW - Statistical data KW - Statistical methods KW - Statistical science KW - Econometrics KW - Statistics . KW - Clinical medicine KW - Clinical pathology KW - Diagnostic laboratory tests KW - Laboratory diagnosis KW - Laboratory medicine KW - Medical laboratory diagnosis KW - Diagnosis KW - Pathology KW - Biometry. KW - Medicine KW - Biology KW - Biostatistics. KW - Biomedical Research. KW - Research. KW - Biological research KW - Biomedical research KW - Health Workforce KW - Biological statistics KW - Biometrics (Biology) KW - Biostatistics KW - Biomathematics KW - Statistics UR - https://www.unicat.be/uniCat?func=search&query=sysid:4865151 AB - The book brings together experts working in public health and multi-disciplinary areas to present recent issues in statistical methodological development and their applications. This timely book will impact model development and data analyses of public health research across a wide spectrum of analysis. Data and software used in the studies are available for the reader to replicate the models and outcomes. The fifteen chapters range in focus from techniques for dealing with missing data with Bayesian estimation, health surveillance and population definition and implications in applied latent class analysis, to multiple comparison and meta-analysis in public health data. Researchers in biomedical and public health research will find this book to be a useful reference, and it can be used in graduate level classes. ER -