Statistical Analytics for Health Data Science w. Wilson, Wilson, Chen, Peace**

Taylor & Francis Ltd

Statistical Analytics for Health Data Science with SAS and R, Two-Volume SetAuthor(s): Jeffrey Wilson, Ding-Geng Chen, Karl E. Peace\nPublisher: Taylor & Francis Ltd, United Kingdom\nImprint: CRC Press\nISBN-13: 9781041089872, 978-1041089872\nSynopsis\nStatistical Analytics for Health Data Science with SAS and R, Two-Volume Set compiles fundamental statistical principles with advanced analytical techniques and covers a wide range of statistical methodologies including models for longitudinal data with time-dependent covariates, multi-membership mixed-effects models, statistical modeling of survival data, Bayesian statistics, joint modeling of longitudinal and survival data, nonlinear regression, statistical meta-analysis, spatial statistics, structural equation modeling, latent growth curve modeling, causal inference and propensity score analysis.\n\nWith an emphasis on real-world applications, the books integrate publicly available health datasets and provide case studies from ae