Biostatistics and Computer-based Analysis of Health Data Using SAS

Author： Lalanne Christophe;Mesbah Mounir

Publication year： 2017

E-ISBN: 9780081011713

P-ISBN(Paperback): 9781785481116

Subject： F224-39 computer applications;O211 probability (probability theory, probability theory);Q811.4 biological information theory;TP1 自动化基础理论;TP3 Computers

Keyword：概率论（几率论、或然率论）,电子计算机的应用,生物信息论,计算技术、计算机技术,自动化基础理论

Language： ENG

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Description

This volume of the Biostatistics and Health Sciences Set focuses on statistics applied to clinical research. The use of SAS for data management and statistical modeling is illustrated using various examples. Many aspects of data processing and statistical analysis of cross-sectional and experimental medical data are covered, including regression models commonly found in medical statistics.

This practical book is primarily intended for health researchers with a basic knowledge of statistical methodology. Assuming basic concepts, the authors focus on the practice of biostatistical methods essential to clinical research, epidemiology and analysis of biomedical data (including comparison of two groups, analysis of categorical data, ANOVA, linear and logistic regression, and survival analysis). The use of examples from clinical trials and epidemiological studies provide the basis for a series of practical exercises, which provide instruction and familiarize the reader with essential SAS commands.

Presents the use of SAS software in the statistical approach for the management of data modeling
Includes elements of the language and descriptive statistics
Supplies measures of association, comparison of means, and proportions for two or more samples
Explores linear and logistic regression
Provides survival data analysis

Chapter

Front Cover

Biostatistics and Computer-based Analysis of Health Data using SAS

Contents

Introduction

1. Language Elements

1.1. Introduction to the SAS language

1.2. Creating and managing SAS tables

1.3. Key points to remember

1.4. Further information

1.5. Applications

2. Simple Descriptive Statistics

2.1. Univariate descriptive statistics: Estimation

2.2. Bivariate descriptive statistics

2.3. Key points to remember

2.4. Further information

2.5. Applications

3. Measures of Association, Comparison of Means or Proportions

3.1. Comparison of two means

3.2. Comparisons of two proportions with independent samples

3.3. Measures of association in a contingency table

3.4. Comparisons of several means

3.5. Key points to remember

3.6. Further information

3.7. Applications

4. Correlation, Linear Regression

4.1. Linear correlation

4.2. Linear regression

4.3. Key points to remember

4.4. Further information

4.5. Applications

5. Logistic Regression

5.1. Logistic regression

5.2. Key points to remember

5.3. Further information

5.4. Applications

6. Survival Curves, Cox Regression

6.1. Survival curves

6.2. Cox regression

6.3. Key points to remember

6.4. Further information

6.5. Applications

Appendices

Appendix A: Introduction to SAS Studio

A.1. Dialogue with Dylan to install SAS Studio

A.2. Comments

Appendix B: Introduction to SAS Macro

B.1. Simple examples of SAS/MACRO programs

B.2. Comments

Appendix C: Introduction to SAS IML

C.1. Example of a SAS/IML program

C.2. Comments

Bibliography

Index

Back Cover

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