Elements of Success

Elements of Success: How Type of Secondary Education Credential Helps Predict Enlistee Attrition

Susan Burkhauser
Lawrence M. Hanser
Chaitra M. Hardison
Copyright Date: 2014
Published by: RAND Corporation
Pages: 63
https://www.jstor.org/stable/10.7249/j.ctt5vjwzx
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  • Book Info
    Elements of Success
    Book Description:

    The U.S. military services have traditionally used a tiering system including education credentials as one element of gauging the likelihood of a recruit persevering through his or her first term of service. To assess the continuing value of this system, the authors compared attrition rates for those with distance learning or homeschool credentials to those of high school diploma holders.

    eISBN: 978-0-8330-8522-1
    Subjects: Business, Management & Organizational Behavior, History

Table of Contents

  1. Front Matter
    (pp. i-ii)
  2. Preface
    (pp. iii-iv)
  3. Table of Contents
    (pp. v-vi)
  4. Figures
    (pp. vii-viii)
  5. Tables
    (pp. ix-x)
  6. Acknowledgments
    (pp. xi-xii)
  7. Abbreviations
    (pp. xiii-xiv)
  8. CHAPTER ONE Introduction
    (pp. 1-4)

    Education credentials in combination with Armed Forces Qualification Test (AFQT) scores (derived from the Armed Services Vocational Aptitude Battery) are the primary elements the U.S. military services use to define enlisted recruit quality. AFQT scores have traditionally been used to predict performance in training and on the job. In contrast, education credentials have traditionally been used to identify candidates who are more likely to attrit during the first term of service. Prior to 2012, three groupings, or tiers, were used to define education credentials. The top tier (Tier 1) consisted of three broad groups: traditional high school diplomas, completion of...

  9. CHAPTER TWO Attrition Analyses
    (pp. 5-16)

    This chapter provides an overview of the data and of the statistical methods used to examine attrition.

    Altogether, the military services enlist over 300,000 individuals per year, but fewer than 0.5 percent of these individuals have homeschool diplomas and 0.1 percent or fewer have distance learning diplomas at enlistment. This meant that we would have to include several cohorts of accessions to obtain a reasonable sample of individuals with these characteristics to analyze. As a result, we sought to obtain data on regular non–prior service enlisted accessions who could have completed at least 12 months of service. We received...

  10. CHAPTER THREE Study Findings
    (pp. 17-20)

    The chapter includes our propensity weighted logistic analysis findings. For comparison purposes, we include results from the simple logistic regression models (i.e., without propensity weights or doubly robust estimation) in Appendix D.

    The analyses presented here are designed to estimate how holding a homeschool diploma or a distance learning diploma affects attrition outcomes. For each of the two of education credentials (homeschool and distance learning), we conducted the same series of analyses.

    Using the homeschool diploma analysis for an example, we compared actual attrition rates for the people with a homeschool diploma to statistical estimates of their attrition rates (i.e.,...

  11. CHAPTER FOUR Conclusions and Recommendations
    (pp. 21-22)

    The goal of this effort was to determine whether applicants who scored less than 50 on the AFQT and have distance learning or homeschool credentials are more likely to attrit than those who scored less than 50 on the AFQT and have high school diplomas (all else being equal). According to our data, the answer is yes, they are more likely to attrit.

    Holding a homeschool diploma instead of a regular high school diploma had significant negative effects on attrition rates. Overall, estimated attrition rates for recruits with homeschool diplomas are slightly, but statistically significantly, higher than attrition rates for...

  12. APPENDIX A Descriptive Statistics for Key Variables
    (pp. 23-30)
  13. APPENDIX B Effectiveness of the Propensity Weights
    (pp. 31-40)
  14. APPENDIX C Models Used in Doubly Robust Regression Analysis
    (pp. 41-42)
  15. APPENDIX D Simple Logistic Regression Model
    (pp. 43-46)
  16. References
    (pp. 47-48)