Reduce the cost and time of cleaning, managing, and preparing research data while also improving data quality! Have you ever wished there was an easy way to reduce your workload and improve the quality of your data? The Data Detective's Toolkit: Cutting-Edge Techniques and SAS Macros to Clean, Prepare, and Manage Data will help you automate many of the labor-intensive tasks needed to turn raw data into high-quality, analysis-ready data. You will find the right tools and techniques in this book to reduce the amount of time needed to clean, edit, validate, and document your data. These tools include SAS macros as well as ingenious ways of using SAS procedures and functions.
The innovative logic built into the book's macro programs enables you to monitor the quality of your data using information from the formats and labels created for the variables in your data set. The book explains how to harmonize data sets that need to be combined and automate data cleaning tasks to detect errors in data including out-of-range values, inconsistent flow through skip paths, missing data, no variation in values for a variable, and duplicates. By the end of this book, you will be able to automatically produce codebooks, crosswalks, and data catalogs.
Industry Reviews
Chantala walks us through the stages of identifying and compiling a record of data quality errors. She shows how this high-level documentation can be automated through the use of macros. The benefit of this technique is that well-constructed macros can accommodate differences in input data. Dissimilarities are not showstoppers. Cleaning, preparing, and managing data from Stage 3 (Acquire Data) all the way to Stage 9 (Archive Project) are under control. Overall, The Data Detective's Toolkit is very well-researched and written.
Jim Sattler
Satmari Software Systems
Manila, Philippines
This book is absolutely packed full of useful information to any user of SAS, whether you're a novice or an expert. Chantala has created a series of macros that allow SAS to provide the user with a huge variety of extraordinarily useful information, from creating codebooks to analyzing data that has skip patterns (also known as conditional logic). You'll be going back to this book over and over again.
Chris Battiston
Research Data Analyst
Women's College Hospital