Predicting U.S. Army First Term Attrition After Initial Entry Training

Abstract

The United States Army recently announced a reduction of its 2018 recruiting goal due to a challenging recruiting environment and a shrinking population of eligible candidates. However, the Sergeant Major of the Army has stated that the current improvement in the retention of existing soldiers should mitigate the loss of new recruits. The goal of this research is to identify demographic and administrative factors of active component, first-term enlisted soldiers who have completed their Initial Entry Training to construct predictive models capable of identifying soldiers with high chances of failure in completing their initial contractual obligation. We construct a binary logistic regression model and a random forest classification model to predict a soldiers probability of first-term attrition based on the individuals unique service record .We find that a soldiers deployment history and the duration of the initial contract are significant predictorsof whether a soldier will complete his or her first term. Knowledge of the key factors and other influencingvariables assists the Army Resiliency Directorate in creation of models and tools to better advise Armyleadership and develop intervention strategies and preventative measures to prevent the loss of first-termsoldiers.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2018
Accession Number
AD1060073

Entities

People

  • Karey J. Speten

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Biomedical
  • Human Systems

DTIC Thesaurus Topics

  • Army Personnel
  • Attrition
  • Data Mining
  • Data Science
  • Databases
  • Education
  • Employment
  • Enlisted Personnel
  • Information Processing
  • Information Science
  • Information Systems
  • Knowledge Management
  • Management Personnel
  • Military Personnel
  • Military Science
  • National Security
  • Personnel Management
  • Predictive Modeling
  • Regression Analysis
  • Statistical Analysis
  • Surveys
  • Training
  • United States

Readers

  • Military Mobilization and Reserve Forces Studies.
  • Naval Personnel Management
  • Systems Analysis and Design