Longitudinal data and SAS : a programmer's guide / Ron Cody.

Format:

Book

Author/Creator:

Cody, Ronald P.

Language:

English

Subjects (All):

SAS (Computer file).

Statistics.

Longitudinal method.

Physical Description:

xx, 174 pages : illustrations ; 23 cm

Place of Publication:

Cary, N.C. : SAS Institute, 2001.

Summary:

This title details useful techniques for conducting operations between observations in a SAS data set. For quick reference, the book is conveniently organized to cover tools, case studies, and macros. Beginning to intermediate SAS users will appreciate this book's informative, easy-to-comprehend style.

Contents:

1 The RETAIN Statement

Demonstrating a DATA Step with and without a RETAIN Statement 1

Generating Sequential SUBJECT Numbers Using a Retained Variable 7

Using a SUM Statement to Create SUBJECT Numbers 9

Demonstrating That Variables Read with a SET Statement Are Retained 10

A Caution When Using a RETAIN Statement 11

2 The LAG and DIF Functions

Using the LAG Function to Compute Differences 13

Demonstrating Some Related Functions: LAG2, LAG3, and So Forth 16

Demonstrating the DIF Function 17

3 FIRST. and LAST. Temporary Variables

How to Create FIRST. and LAST. Temporary Variables 19

Using More Than One BY Variable 22

A Simple Application Using FIRST. and LAST. Variables 24

4 Flags and Counters

Using a Flag Variable to Determine If a Particular Event Ever Occurred in Any One of Several Observations for Each Subject 27

Counting the Number of Positive Outcomes for Each Patient 29

5 Summarizing Data Using PROC MEANS and PROC FREQ

Using PROC MEANS to Output Means to a Data Set 34

Comparing CLASS and BY Statements with PROC MEANS 37

Computing Other Descriptive Statistics 38

Automatically Naming the Variables in the Output Data Set 40

Demonstrating an Alternative Way to Select Specific Descriptive Statistics for Selected Variables 41

Adding Additional Variables to the Summary Data Set Using an ID Statement 42

Specifying More Than One CLASS Variable 44

Selecting Multi-Way Breakdowns Using the TYPES Statement 47

Using the PROC MEANS CHARTYPE Option to Simplify the _TYPE_ Interpretation 49

Comparing PROC MEANS and PROC FREQ for Creating an Output Data Set Containing Counts 50

Counting Frequencies for a Two-Way Table 52

6 Using PROC SQL with Longitudinal Data

Creating a Demonstration Data Set 55

A Simple SQL Query 57

Using PROC SQL to Count Observations within a BY Group 58

Demonstrating a HAVING Clause 59

Using PROC SQL to Create a Macro Variable 60

Using a Summary Function to Compute Group Means 62

7 Restructuring SAS Data Sets Using Arrays

Creating a New Data Set with Several Observations per Subject from a Data Set with One Observation per Subject 66

Another Example of Creating Multiple Observations from a Single Observation 69

Going from One Observation per Subject to Many Observations per Subject Using Multidimensional Arrays 72

Demonstrating the Use of a Multidimensional Array 74

An Alternative Program 77

Another Example of a Multidimensional Array 78

8 Restructuring SAS Data Sets Using PROC TRANSPOSE

Going from One Observation to Several Observations 81

Another Example of Creating Multiple Observations from a Single Observation 84

Going from One Observation per Subject to Many Observations per Subject 86

Creating a Data Set with One Observation per Subject from a Data Set with Multiple Observations per Subject 88

9 Study One: Operations on a Clinical Database

Description of the Clinical Data Set 94

Selecting the First or Last Visit for Each Patient 95

Computing Differences between the First and Last Visits 97

Another Method of Computing Differences between the First and Last Visits 99

Computing Differences between Every Visit 100

Counting the Number of Visits for Each Patient (DATA Step Approach) 101

Counting the Number of Visits for Each Patient (PROC FREQ) 103

Counting the Number of Visits for Each Patient (PROC MEANS) 103

Counting the Number of Visits for Each Patient (PROC SQL) 104

Selecting All Patients with n Visits (DATA Step Approach) 105

Selecting All Patients with n Visits (PROC FREQ Approach) 106

Selecting All Patients with Two Visits (Using PROC SQL) 107

Selecting All Patients with Two Visits (Using SQL in One Step) 107

Using PROC SQL to Create a Macro Variable 108

Computing Summary Statistics for Each Patient (Using PROC MEANS) 109

Computing Summary Statistics for Each Patient (Using PROC SQL) 110

Adding a Value from the First Visit to Each Subsequent Visit 111

Looking Ahead: Making a Decision about the Current Observation Based on Information in the Next Observation 114

Using Flags to Ascertain Vitamin Use 117

Using PROC FREQ to Ascertain Vitamin Use 118

Counting the Number of Routine Visits for Each Patient 119

10 Study Two: Operations on Daily Weather Data and Ozone Levels

The OZONE Data Set 121

Computing Weekly Averages 122

Using the MOD Function to Group Data Values 125

Computing a Moving Average for a Single Variable 127

11 Study Three: Producing Summary Reports on a Library Data Set

Computing the Number of Books per Patron Visit and by Library 130

Computing the Number of Patrons by Day of Week and Library 134

Generating a Table of LC Categories by Age Group and Overall 135

12 Useful Macros

Listing All or Part of a Data Set 141

Computing Differences between Successive Observations 143

Computing Differences between the First and Last Observations per Subject 145

Computing a Moving Average 147

Computing Cell Means and Counts 149

Counting the Number of Observations per Subject 151

Appendix List of Data Files and SAS Data Sets

The TEST_SCORES Data Set 153

The CLINICAL Data Set 154

The CLIN_FIRST Data Set 156

The OZONE Data Set 157

The LIBRARY Data Set 160.

Notes:

Includes index.

ISBN:

1580259243

OCLC:

49829285