An Examination into Retention Behavior of Air Force Female Officers

Abstract

Female retention rates in the US military have been considerably lower than that of their male counterparts for numerous years. In the Air Force, women represent 14 percent of officer ranks from O-5 level and above. Comparatively, the overall rate of women officers in service is 20 percent. Understanding the negative factors associated with the attrition rate of this group can help the Air Force leverage positive change. It may also influence adjustments that will increase the number of women serving, and improve diversity throughout both the officer and enlisted ranks. In this study, logistic regression and survival analysis are applied to model retention and some understanding of how to diversify the Air Force, through increasing our female officer population. Demographic, organizational, and political elements are considered to ensure all affecting issues are measured. Programs that have gone into effect in the past five years, such as the Force of theFuture, and Blended Retirement, are also considered to determine their statistical significance. Applying logistic regression determines potential factors affecting retention rates. All elements are include in survival analysis to characterize female officer retention behavior. Implementing and providing such analysis will help generate a prediction model for retention rates amongst female officers, and how to further amplify diversity.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2021
Accession Number
AD1130264

Entities

People

  • Jessica M Astudillo

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Biomedical
  • Human Systems
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Air Force Personnel
  • Attrition
  • Business Administration
  • Combat Support
  • Data Sets
  • Department Of Defense
  • Employment
  • Engineering
  • Governments
  • Information Warfare
  • Law
  • Literature Surveys
  • Management Personnel
  • Military Personnel
  • Military Science
  • Motivation
  • National Security
  • Personnel Management
  • Predictive Modeling
  • Regression Analysis
  • Security
  • Statistical Analysis
  • United States
  • United States Government
  • Warfare

Readers

  • Gender and Food Studies
  • Naval Personnel Management
  • Systems Analysis and Design