Managing Your Research Data and Documentation

Edition: 1st
Format: Paperback
Pub. Date: 2017-11-13
Publisher(s): American Psychological Association
List Price: $31.95

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Choice Reviews Outstanding Academic Title

In the behavioral sciences today, there is increasing emphasis on transparency, and the need for research studies to be made replicable. This book presents a straightforward approach to managing and documenting one’s data so that other researchers can repeat the study.
While data management may seem intimidating to new researchers, this book shows how easy it can (and should!) be. The first chapter presents a basic structure of folders and subfolders for organizing data files, and then each subsequent chapter delves into details for a specific folder. Step by step, readers learn to label and archive different kinds of project documents and data files, including original, processed, and working data. Readers also learn to write command codes showing exactly how the original data are analyzed. Examples illustrate how to document the most common types of research (an online survey, a paper questionnaire, and a multiple-trial experiment).
Since major research funders now require recipients to meet strict standards for data handling, this book will foster a vital career skill for students and promote transparency and replicability of research.

Author Biography

Kathy R. Berenson, PhD, is assistant professor of psychology at Gettysburg College and a clinical psychologist who conducts research focused on cognitive/affective and interpersonal factors in psychological difficulties. She has many years of experience managing data for large, grant-funded studies and mentoring undergraduate research in the fields of personality and psychopathology.

Table of Contents

Series Foreword
Chapter 1. Introduction
Chapter 2. Your Project Files
Chapter 3. Your Data Files
Chapter 4. Your Command Files
Chapter 5. Your Replication Documentation
Appendix A. Source Data and Metadata
Appendix B. Working With “Tall” Data Files
Appendix C. Data Entry
Appendix D. Labeling and Renaming Many Variables Efficiently
Appendix E. Importing Data Files
Appendix F. Merging Data Files
Appendix G. Estimating Missing Values
About the Author
About the Series Editor

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