Airman Applicant Prediction System (AAPS): Theory and Results

Abstract : The objective of this research effort was to design a model(s) to estimate the impact of key demographic variables on individual and group accession behavior. This would provide personnel managers the ability to project the quality mix of future accessions and track the impact of this quality mix on enlisted retention behavior as these accessions advance through a military career. Six demographic groups were analyzed: males, females, Caucasians, Blacks, others, and all. Within each demographic group, four aptitude groups were studied: Armed Forces Qualifying Test (AFQT) Categories I's, II's, IIa's, and IIb's. The results of the modeling and estimation effort were implemented into the Airman Applicant Prediction System (AAPS) to predict the number of applicants from selected demographic/aptitude groups. The estimated equations were used to predict the proportion of a Military Available (MA) population which would be interested in applying to the Air Force (by AFQT Category). AAPS proceeds through a series of steps to arrive at population numbers for Interested Qualified Military Available (IQMA). IQMA can then be disaggregated through the AAPS software to determine from the IQMA population who would potentially meet mechanical, administrative, general, and electronic (MAGE) minimum Armed Services Vocational Aptitude Battery (ASVAB) composite score requirements. Applicant prediction, Enlisted force projection model, Demographic applicant breakout, Military available