Predicting US Army First-Term Attrition After Initial Entry Training

Abstract

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 models to predict the probability of failure in completing their initial contractual obligation. We construct a binary logistic regression model, classification tree and a random forest classification model to predict a soldiers probability of first-term attrition based on the individuals unique service record. We design web based graphic user interface that allows leaders, soldiers or recruiters to input demographic variables of current soldiers or recruits and get the predicted probability of attrition as an output. We find that a soldiers deployment history and the duration of the initial contract are significant predictors of whether a soldier will complete his or her first term. Knowledge of the key factors, and other influencing variables, assists the Army Resiliency Directorate in creation of models and tools to better advise U.S. Army leadership and development of intervention strategies and preventative measures to preclude the loss of first-term soldiers.

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Document Details

Document Type
Technical Report
Publication Date
Jun 30, 2018
Accession Number
AD1063055

Entities

People

  • Andrew Anglemyer
  • Anthony D. Smith
  • Jarrod Shingleton
  • Jon Alt
  • Karey Speten

Tags

Communities of Interest

  • Engineered Resilient Systems
  • Human Systems

DTIC Thesaurus Topics

  • Army Personnel
  • Attrition
  • Data Mining
  • Databases
  • Education
  • Employment
  • Enlisted Personnel
  • Information Processing
  • Information Science
  • Information Systems
  • Management Personnel
  • Military Personnel
  • Military Science
  • Organizational Structure
  • Personnel Management
  • Supervised Machine Learning
  • Training

Readers

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