SAS and R: Data Management, Statistical Analysis, and Graphics / Edition 1 by Ken Kleinman, Nicholas J. Horton | | 9781420070576 | Hardcover | Barnes & Noble
SAS and R: Data Management, Statistical Analysis, and Graphics / Edition 1

SAS and R: Data Management, Statistical Analysis, and Graphics / Edition 1

by Ken Kleinman, Nicholas J. Horton
     
 

ISBN-10: 1420070576

ISBN-13: 9781420070576

Pub. Date: 07/17/2009

Publisher: Taylor & Francis

An All-in-One Resource for Using SAS and R to Carry out Common Tasks

Provides a path between languages that is easier than reading complete documentation
SAS and R: Data Management, Statistical Analysis, and Graphics presents an easy way to learn how to perform an analytical task in both SAS and R, without having to navigate

Overview

An All-in-One Resource for Using SAS and R to Carry out Common Tasks

Provides a path between languages that is easier than reading complete documentation
SAS and R: Data Management, Statistical Analysis, and Graphics presents an easy way to learn how to perform an analytical task in both SAS and R, without having to navigate through the extensive, idiosyncratic, and sometimes unwieldy software documentation. The book covers many common tasks, such as data management, descriptive summaries, inferential procedures, regression analysis, and the creation of graphics, along with more complex applications.

Takes an innovative, easy-to-understand, dictionary-like approach
Through the extensive indexing, cross-referencing, and worked examples in this text, users can directly find and implement the material they need. The book enables easier mobility between the two systems: SAS users can look up tasks in the SAS index and then find the associated R code while R users can benefit from the R index in a similar manner. Demonstrating the code in action and facilitating exploration, the authors present extensive example analyses that employ a single data set from the HELP study. They offer the data sets and code for download on the book’s website.

Product Details

ISBN-13:
9781420070576
Publisher:
Taylor & Francis
Publication date:
07/17/2009
Edition description:
New Edition
Pages:
343
Product dimensions:
7.20(w) x 10.10(h) x 1.00(d)

Table of Contents

Data Management

Input

Output

Structure and Meta-Data

Derived Variables and Data Manipulation

Merging, Combining, and Subsetting Data Sets

Date and Time Variables

Interactions with the Operating System

Mathematical Functions

Matrix Operations

Probability Distributions and Random Number Generation

Control Flow, Programming, and Data Generation

Common Statistical Procedures

Summary Statistics

Bivariate Statistics

Contingency Tables

Two Sample Tests for Continuous Variables

Linear Regression and ANOVA

Model Fitting

Model Comparison and Selection

Tests, Contrasts, and Linear Functions of Parameters

Model Diagnostics

Model Parameters and Results

Regression Generalizations

Generalized Linear Models

Models for Correlated Data

Survival Analysis

Further Generalizations to Regression Models

Graphics

A Compendium of Useful Plots

Adding Elements

Options and Parameters

Saving Graphs

Other Topics and Extended Examples

Power and Sample Size Calculations

Generate Data from Generalized Linear Random Effects Model

Generate Correlated Binary Data

Read Variable Format Files and Plot Maps

Missing Data: Multiple Imputation

Bayesian Poisson Regression

Multivariate Statistics and Discriminant Procedures

Complex Survey Design

Appendix A: Introduction to SAS

Installation

Running SAS and a Sample Session

Learning SAS and Getting Help

Fundamental Structures: Data Step, Procedures, and Global Statements

Work Process: The Cognitive Style of SAS

Useful SAS Background

Accessing and Controlling SAS Output: The Output Delivery System

The SAS Macro Facility: Writing Functions and Passing Values

Miscellanea

Appendix B: Introduction to R

Installation

Running R and Sample Session

Learning R and Getting Help

Fundamental Structures: Objects, Classes, and Related Concepts

Built-in and User-Defined Functions

Add-ons: Libraries and Packages

Support and Bugs

Appendix C: The HELP Study Data Set

Background on the HELP Study

Roadmap to Analyses of the HELP Data Set

Detailed Description of the Data Set

Appendix D: References

Appendix E: Indices

Subject Index

SAS Index

R Index

Further Resources and HELP Examples appear at the end of each chapter.

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