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<p>The Marine Corps expends much effort and money annually in recruiting qualified applicants to fill its ranks. Yet, an average of one out of every five new recruits leaves the Delayed Entry Program (DEP) even before attending boot camp. This thesis uses binary probit models to analyze four years of enlistment data obtained through the Total Force Data Warehouse (TFDW) from five of the six Marine Corps Districts (MCDs). The study first investigates whether the discharge probability of a new recruit varies by the day of the month in which the recruit signs an enlistment contract. Building on this relationship, the thesis then analyzes attrition prediction variables to differentiate recruits who exhibit a disproportionately high attrition risk from those who do not. Results show that a recruit's attrition risk does increase dramatically with the approach of the monthly deadline. Additionally, recruits who exhibit a high risk of attrition can be identified using current enlistment criteria. With the information provided by this thesis, the Marine Corps can effectively target high-risk recruits and thereby lower its DEP attrition.
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<br>Subjects: Manpower</div>
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Bruno, Michael G.</div>
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