Book description
Working with longitudinal data introduces a unique set of challenges. Once you've mastered the art of performing calculations within a single observation of a data set, you're faced with the task of performing calculations or making comparisons between observations. It's easy to look backward in data sets, but how do you look forward and across observations? Ron Cody provides straightforward answers to these and other questions. Longitudinal Data and SAS details useful techniques for conducting operations between observations in a SAS data set. For quick reference, the book is conveniently organized to cover tools, including an introduction to powerful SAS programming techniques for longitudinal data; case studies, including a variety of illuminating examples that use Ron's techniques; and macros, including detailed descriptions of helpful longitudinal data macros. Beginning to intermediate SAS users will appreciate this book's informative, easytocomprehend style. And users who frequently process longitudinal data will learn to make the most of their analyses by following Ron's methodologies. This book is part of the SAS Press program.Table of contents
 List of Programs
 Preface

Acknowledgments
 1 The RETAIN Statement
 Introduction
 Demonstrating a DATA Step with and without a RETAIN Statement
 Generating Sequential SUBJECT Numbers Using a Retained Variable
 Using a SUM Statement to Create SUBJECT Numbers
 Demonstrating That Variables Read with a SET Statement Are Retained
 A Caution When Using a RETAIN Statement
 2 The LAG and DIF Functions
 3 FIRST. and LAST. Temporary Variables
 4 Flags and Counters

5 Summarizing Data Using PROC MEANS and PROC FREQ
 Introduction
 Using PROC MEANS to Output Means to a Data Set
 Comparing CLASS and BY Statements with PROC MEANS
 Computing Other Descriptive Statistics
 Automatically Naming the Variables in the Output Data Set
 Demonstrating an Alternative Way to Select Specific Descriptive Statistics for Selected Variables
 Adding Additional Variables to the Summary Data Set Using an ID Statement
 Specifying More Than One CLASS Variable
 Selecting MultiWay Breakdowns Using the TYPES Statement
 Using the PROC MEANS CHARTYPE Option to Simplify the _TYPE_ Interpretation
 Comparing PROC MEANS and PROC FREQ for Creating an Output Data Set Containing Counts
 Counting Frequencies for a TwoWay Table
 6 Using PROC SQL with Longitudinal Data

7 Restructuring SAS Data Sets Using Arrays
 Introduction
 Creating a New Data Set with Several Observations per Subject from a Data Set with One Observation per Subject
 Another Example of Creating Multiple Observations from a Single Observation
 Going from One Observation per Subject to Many Observations per Subject Using Multidimensional Arrays
 Demonstrating the Use of a Multidimensional Array
 An Alternative Program
 Another Example of a Multidimensional Array

8 Restructuring SAS Data Sets Using PROC TRANSPOSE
 Introduction
 Going from One Observation to Several Observations
 Another Example of Creating Multiple Observations from a Single Observation
 Going from One Observation per Subject to Many Observations per Subject
 Creating a Data Set with One Observation per Subject from a Data Set with Multiple Observations per Subject

9 Study One: Operations on a Clinical Database
 Introduction
 Description of the Clinical Data Set
 Selecting the First or Last Visit for Each Patient
 Computing Differences between the First and Last Visits
 Another Method of Computing Differences between the First and Last Visits
 Computing Differences between Every Visit
 Counting the Number of Visits for Each Patient (DATA Step Approach
 Counting the Number of Visits for Each Patient (PROC FREQ)
 Counting the Number of Visits for Each Patient (PROC MEANS)
 Counting the Number of Visits for Each Patient (PROC SQL)
 Selecting All Patients with nVisits (DATA Step Approach)
 Selecting All Patients with nVisits (PROC FREQ Approach)
 Selecting All Patients with Two Visits (Using PROC SQL)
 Selecting All Patients with Two Visits (Using SQL in One Step)
 Using PROC SQL to Create a Macro Variable
 Computing Summary Statistics for Each Patient (Using PROC MEANS
 Computing Summary Statistics for Each Patient (Using PROC SQL
 Adding a Value from the First Visit to Each Subsequent Visit
 Looking Ahead: Making a Decision about the Current Observation Based on Information in the Next Observation
 Using Flags to Ascertain Vitamin Use
 Using PROC FREQ to Ascertain Vitamin Use
 Counting the Number of Routine Visits for Each Patient
 10 Study Two: Operations on Daily Weather Data and Ozone Levels
 11 Study Three: Producing Summary Reports on a Library Data Set
 12 Useful Macros
 Appendix List of List of Data Files and SAS Data Sets
 Index
Product information
 Title: Longitudinal Data and SAS
 Author(s):
 Release date: October 2001
 Publisher(s): SAS Institute
 ISBN: 9781629592497
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