Statistical Analysis of Medical Data Using SAS

Statistical Analysis of Medical Data Using SAS

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Description

Statistical analysis is ubiquitous in modern medical research. Logistic regression, generalized linear models, random effects models, and Cox's regression all have become commonplace in the medical literature. But while statistical software such as SAS make routine application of these techniques possible, users who are not primarily statisticians must take care to correctly implement the various procedures and correctly interpret the output. "Statistical Analysis of Medical Data Using SAS" demonstrates how to use SAS to analyze medical data. Each chapter addresses a particular analysis method.The authors briefly describe each procedure, but focus on its SAS implementation and properly interpreting the output. The carefully designed presentation relegates the theoretical details to 'Displays', so that the code and results can be explored without interruption. All of the code and data sets used in the book are available for download from either the SAS Web site. Der and Everitt, authors of the best-selling "Handbook of Statistical Analyses Using SAS", bring all of their considerable talent and experience to bear in this book. Step-by-step instructions, lucid explanations and clear examples combine to form an outstanding, self-contained guide - suitable for medical researchers and statisticians alike - to using SAS to analyze medical data.show more

Product details

  • Hardback | 440 pages
  • 154.9 x 236.2 x 30.5mm | 771.12g
  • Taylor & Francis Ltd
  • Chapman & Hall/CRC
  • Boca Raton, FL, United States
  • English
  • 107 black & white illustrations, 117 black & white tables
  • 158488469X
  • 9781584884699
  • 1,245,639

Table of contents

An Introduction to SAS Describing and Summarizing Data Basic Inference Scatterplots Correlation: Simple Regression and Smoothing Analysis of Variance and Covariance Multiple Regression Logistic Regression The Generalized Linear Model Generalized Additive Models Nonlinear Regression Models The Analysis of Longitudinal Data I The Analysis of Longitudinal Data II: Models for Normal Response Variables The Analysis of Longitudinal Data III: Non-Normal Response Survival Analysis Analysis Multivariate Date: Principal Components and Cluster Analysis Referencesshow more

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