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Cody's Data Cleaning Techniques Using SAS Software / Edition 1

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More About This Textbook

Overview

The key to ensuring accurate data is having clean data. This book develops and describes data cleaning programs and macros. You can use many of the programs and macros that are provided, as is, or you can modify them for your own special data cleaning tasks. Ron has carefully explained and documented each of the programs and macros, thus providing you with SAS programming instruction on an intermediate-to-advanced level. Topics presented include validation checks on character data, numeric data, missing values, and date values; searching for duplicate records; working with multiple files; double entry and verification using the COMPARE procedure; and SQL solutions and using validation data sets. Written in Ron's signature informal, tutorial style, this book gives anyone who manages data thoroughly documented, step-by-step instructions for the development of data cleaning programs and macros. Supports releases 6.12 and higher of SAS software.
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Product Details

  • ISBN-13: 9781580256001
  • Publisher: SAS Publishing
  • Publication date: 1/7/2000
  • Edition description: Older Edition
  • Edition number: 1
  • Pages: 230
  • Product dimensions: 7.60 (w) x 9.20 (h) x 0.60 (d)

Table of Contents

List of Programs ix
Introduction xvii
Acknowledgments xix
1 Checking Values of Character Variables
Introduction 1
Using PROC FREQ to List Values 1
Description of the File PATIENTS.TXT 2
Using a DATA Step to Check for Invalid Values 6
Using PROC PRINT with a WHERE Statement to List Invalid Values 11
Using Formats to Check for Invalid Values 13
Using Informats to Check for Invalid Values 17
2 Checking Values of Numeric Variables
Introduction 21
Using PROC MEANS, PROC TABULATE, and PROC UNIVARIATE to Look for Outliers 22
Using PROC PRINT with a WHERE Statement to List Invalid Data Values 32
Using a DATA Step to Check for Invalid Values 33
Creating a Macro for Range Checking 34
Using Formats to Check for Invalid Values 37
Using Informats to Check for Invalid Values 40
Using PROC UNIVARIATE to Look for Highest and Lowest Values by Percentage 43
Using PROC RANK to Look for Highest and Lowest Values by Percentage 48
Extending PROC RANK to Look for Highest and Lowest "n" Values 51
Finding Another Way to Determine Highest and Lowest Values 55
Checking a Range Using an Algorithm Based on Standard Deviation 58
Macros Based on the Two Methods of Outlier Detection 62
Demonstrating the Difference between the Two Methods 64
Checking a Range Based on the Interquartile Range 65
Checking Ranges for Several Variables 68
3 Checking for Missing Values
Introduction 73
Inspecting the SAS Log 73
Using PROC MEANS and PROC FREQ to Count Missing Values 76
Using DATA Step Approaches to Identify and Count Missing Values 78
Using PROC TABULATE to Count Missing and Nonmissing Values for Numeric Variables 82
Using PROC TABULATE to Count Missing and Nonmissing Values for Character Variables 83
Creating a General Purpose Macro to Count Missing and Nonmissing Values for Both Numeric and Character Variables 84
Searching for a Specific Numeric Value 88
4 Working with Dates
Introduction 93
Checking Ranges for Dates (Using a DATA Step) 94
Checking Ranges for Dates (Using PROC PRINT) 95
Checking for Invalid Dates 95
Working with Dates in Nonstandard Form 99
Creating a SAS Date When the Day of the Month Is Missing 101
Suspending Error Checking for Known Invalid Dates 103
5 Looking for Duplicates and "n" Observations per Subject
Introduction 105
Eliminating Duplicates by Using PROC SORT 105
Detecting Duplicates by Using DATA Step Approaches 110
Using PROC FREQ to Detect Duplicate ID's 113
Selecting Patients with Duplicate Observations by Using a Macro List and SQL 115
Identifying Subjects with "n" Observations Each (DATA Step Approach) 117
Identifying Subjects with "n" Observations Each (Using PROC FREQ) 119
6 Working with Multiple Files
Introduction 121
Checking for an ID in Each of Two Files 121
Checking for an ID in Each of "n" Files 124
A Simple Macro to Check ID's in Multiple Files 126
A More Complicated Multi-File Macro for ID Checking 129
More Complicated Multi-File Rules 131
Checking That the Dates Are in the Proper Order 134
7 Double Entry and Verification (PROC COMPARE)
Introduction 137
Conducting a Simple Comparison of Two Data Sets without an ID Variable 138
Using PROC COMPARE with an ID Variable 144
Using PROC COMPARE with Two Data Sets That Have an Unequal Number of Observations 146
Comparing Two Data Sets When Some Variables Are Not in Both Data Sets 149
8 Some SQL Solutions to Data Cleaning
Introduction 153
A Quick Review of PROC SQL 154
Checking for Invalid Character Values 155
Checking for Outliers 156
Checking a Range Using an Algorithm Based on the Standard Deviation 158
Checking for Missing Values 159
Range Checking for Dates 161
Checking for Duplicates 162
Identifying Subjects with "n" Observations Each 163
Checking for an ID in Each of Two Files 163
More Complicated Multi-File Rules 165
9 Using Validation Data Sets
Introduction 169
A Simple Example of a Validation Data Set 169
Making the Program More Flexible and Converting It to a Macro 174
Validating Character Data 180
Converting Program 9-7 into a General Purpose Macro 187
Extending the Validation Macro to Include Valid Character Ranges 191
Combining Numeric and Character Validity Checks in a Single Macro with a Single Validation Data Set 197
Introducing SAS Integrity Constraints (Versions 7 and Later) 207
Appendix Listing of Raw Data Files and SAS Programs
Description of the Raw Data File PATIENTS.TXT 213
Layout for the Data File PATIENTS.TXT 214
Listing of Raw Data File PATIENTS.TXT 215
Program to Create the SAS Data Set PATIENTS 216
Listing of Raw Data File PATIENTS2.TXT 217
Program to Create the SAS Data Set PATIENTS2 217
Program to Create the SAS Data Set AE (Adverse Events) 218
Program to Create the SAS Data Set LAB_TEST 219
Index 221
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