Longitudinal Data and SAS: A Programmer's Guide

✍ Scribed by Ronald P. Cody

• Publisher: SAS Publishing
• Year: 2001
• Tongue: English
• Leaves: 209
• Edition: 1
• Category: Library

✦ Synopsis

I have to give a very positive review to this book. Cody writes very nice introductory applied statistics books that emphasize SAS applications. This has good illustrations of a very important type of data analysis that biostatisticians doing clinical research need to know. Also, because in the analysis of clinical trials the FDA prefers analysis to be done using SAS, applications in SAS are important to have. If some or even most of this material is covered in another text as one reviewer suggests that does not mean that the biostatistician might not prefer to select this text which concentrates solely on longitudinal data. Also in the pharmaceutical industry where many clinical trials are conducted on longitudinal data, SAS programmers who are not statisticians are employed and books like this one can be of great use to them in their careers. The correct use of PROC Mixed in the analysis of longitudinal data is tricky and mistakes are easy to make.

✦ Table of Contents

FIRST. and LAST. Temporary Variables......Page 6
Summarizing Data Using PROC MEANS and PROC FREQ......Page 7
Restructuring SAS Data Sets Using Arrays......Page 8
Study One: Operations on a Clinical Database......Page 9
Study Three: Producing Summary Reports on a Library Data Set......Page 10
List of Data Files and SAS Data Sets......Page 11
FIRST. and LAST. Temporary Variables......Page 12
Summarizing Data Using PROC MEANS and PROC FREQ......Page 13
Restructuring SAS Data Sets Using Arrays......Page 14
Restructuring SAS Data Sets Using PROC TRANSPOSE......Page 15
Study One: Operations on a Clinical Database......Page 16
Study Two: Operations on Daily Weather Data and Ozone Levels......Page 17
Useful Macros......Page 18
List of Data Files and SAS Data Sets......Page 19
Demonstrating a DATA Step with and without a RETAIN Statement......Page 24
Generating Sequential SUBJECT Numbers Using a Retained Variable......Page 30
Using a SUM Statement to Create SUBJECT Numbers......Page 32
Demonstrating That Variables Read with a SET Statement Are Retained......Page 33
A Caution When Using a RETAIN Statement......Page 34
Using the LAG Function to Compute Differences......Page 36
Demonstrating Some Related Functions: LAG2, LAG3, and So Forth......Page 39
Demonstrating the DIF Function......Page 40
How to Create FIRST. and LAST. Temporary Variables......Page 42
Using More Than One BY Variable......Page 45
A Simple Application Using FIRST. and LAST. Variables......Page 47
Using a Flag Variable to Determine If a Particular Event Ever Occurred in Any One of Several Observations for Each Subject......Page 50
Counting the Number of Positive Outcomes for Each Patient......Page 52
Introduction......Page 56
Using PROC MEANS to Output Means to a Data Set......Page 57
Comparing CLASS and BY Statements with PROC MEANS......Page 60
Computing Other Descriptive Statistics......Page 61
Automatically Naming the Variables in the Output Data Set......Page 63
Demonstrating an Alternative Way to Select Specific Descriptive Statistics for Selected Variables......Page 64
Adding Additional Variables to the Summary Data Set Using an ID Statement......Page 65
Specifying More Than One CLASS Variable......Page 67
Selecting Multi-Way Breakdowns Using the TYPES Statement......Page 70
Using the PROC MEANS CHARTYPE Option to Simplify the _ TYPE_ Interpretation......Page 72
Comparing PROC MEANS and PROC FREQ for Creating an Output Data Set Containing Counts......Page 73
Counting Frequencies for a Two-Way Table......Page 75
Creating a Demonstration Data Set......Page 78
A Simple SQL Query......Page 80
Using PROC SQL to Count Observations within a BY Group......Page 81
Demonstrating a HAVING Clause......Page 82
Using PROC SQL to Create a Macro Variable......Page 83
Using a Summary Function to Compute Group Means......Page 85
Introduction......Page 88
Creating a New Data Set with Several Observations per Subject from a Data Set with One Observation per Subject......Page 89
Another Example of Creating Multiple Observations from a Single Observation......Page 92
Going from One Observation per Subject to Many Observations per Subject Using Multidimensional Arrays......Page 95
Demonstrating the Use of a Multidimensional Array......Page 97
An Alternative Program......Page 100
Another Example of a Multidimensional Array......Page 101
Going from One Observation to Several Observations......Page 104
Another Example of Creating Multiple Observations from a Single Observation......Page 107
Going from One Observation per Subject to Many Observations per Subject......Page 109
Creating a Data Set with One Observation per Subject from a Data Set with Multiple Observations per Subject......Page 111
Description of the Clinical Data Set......Page 117
Selecting the First or Last Visit for Each Patient......Page 118
Computing Differences between the First and Last Visits......Page 120
Another Method of Computing Differences between the First and Last Visits......Page 122
Computing Differences between Every Visit......Page 123
Counting the Number of Visits for Each Patient (DATA Step Approach)......Page 124
Counting the Number of Visits for Each Patient ( PROC MEANS)......Page 126
Counting the Number of Visits for Each Patient ( PROC SQL)......Page 127
Visits (DATA Step Approach)......Page 128
Visits (PROC FREQ Approach)......Page 129
Selecting All Patients with Two Visits (Using SQL in One Step)......Page 130
Using PROC SQL to Create a Macro Variable......Page 131
Computing Summary Statistics for Each Patient (Using PROC MEANS)......Page 132
Computing Summary Statistics for Each Patient (Using PROC SQL)......Page 133
Adding a Value from the First Visit to Each Subsequent Visit......Page 134
Looking Ahead: Making a Decision about the Current Observation Based on Information in the Next Observation......Page 137
Using Flags to Ascertain Vitamin Use......Page 140
Using PROC FREQ to Ascertain Vitamin Use......Page 141
Counting the Number of Routine Visits for Each Patient......Page 142
The OZONE Data Set......Page 144
Computing Weekly Averages......Page 145
Using the MOD Function to Group Data Values......Page 148
Computing a Moving Average for a Single Variable......Page 150
Introduction......Page 154
Computing the Number of Books per Patron Visit and by Library......Page 155
Computing the Number of Patrons by Day of Week and Library......Page 158
Generating a Table of LC Categories by Age Group and Overall......Page 160
Listing All or Part of a Data Set......Page 164
Computing Differences between Successive Observations......Page 166
Computing Differences between the First and Last Observations per Subject......Page 168
Computing a Moving Average......Page 170
Computing Cell Means and Counts......Page 172
Counting the Number of Observations per Subject......Page 174
The TEST_SCORES Data Set......Page 176
The CLINICAL Data Set......Page 177
The CLIN_FIRST Data Set......Page 179

✦ Subjects

Библиотека;Компьютерная литература;SAS / JMP;