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SAS for Epidemiologists

Applications and Methods

  • Charles DiMaggio

Table of contents

  1. Front Matter
    Pages i-xvii
  2. Charles DiMaggio
    Pages 1-5
  3. Working with Data in SAS

    1. Front Matter
      Pages 7-7
    2. Charles DiMaggio
      Pages 9-18
    3. Charles DiMaggio
      Pages 19-40
    4. Charles DiMaggio
      Pages 41-55
    5. Charles DiMaggio
      Pages 57-76
  4. Descriptive and Categorical Analysis

    1. Front Matter
      Pages 77-77
    2. Charles DiMaggio
      Pages 79-89
    3. Charles DiMaggio
      Pages 91-98
    4. Charles DiMaggio
      Pages 99-118
    5. Charles DiMaggio
      Pages 119-135
  5. Continuous Data and Regression

    1. Front Matter
      Pages 137-137
    2. Charles DiMaggio
      Pages 159-186
    3. Charles DiMaggio
      Pages 187-195
    4. Charles DiMaggio
      Pages 197-212
    5. Charles DiMaggio
      Pages 213-229
  6. Back Matter
    Pages 231-258

About this book

Introduction

This comprehensive text covers the use of SAS for epidemiology and public health research. Developed with students in mind and from their feedback, the text addresses this material in a straightforward manner with a multitude of examples. It is directly applicable to students and researchers in the fields of public health, biostatistics and epidemiology. Through a “hands on” approach to the use of SAS for a broad number of epidemiologic analyses, readers learn techniques for data entry and cleaning, categorical analysis, ANOVA, and linear regression and much more. Exercises utilizing real-world data sets are featured throughout the book. SAS screen shots demonstrate the steps for successful programming.

SAS (Statistical Analysis System) is an integrated system of software products provided by the SAS institute, which is headquartered in California. It provides programmers and statisticians the ability to engage in many sophisticated statistical analyses and data retrieval and mining exercises. SAS is widely used in the fields of epidemiology and public health research, predominately due to its ability to reliably analyze very large administrative data sets, as well as more commonly encountered clinical trial and observational research data.   

Keywords

Bioinformatics Clinical Trials Epidemiology Observational Studies SAS

Authors and affiliations

  • Charles DiMaggio
    • 1
  1. 1., Dept of Anesthesiology & EpidemiologyColumbia UniversityNew YorkUSA

Bibliographic information