File:PREDICTING U.S. ARMY FIRST-TERM ATTRITION AFTER INITIAL ENTRY TRAINING, PART II (IA predictingusarmy1094564167).pdf
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PREDICTING U.S. ARMY FIRST-TERM ATTRITION AFTER INITIAL ENTRY TRAINING, PART II
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| Author |
Gobea, Gabriel A. |
| Title |
PREDICTING U.S. ARMY FIRST-TERM ATTRITION AFTER INITIAL ENTRY TRAINING, PART II |
| Publisher |
Monterey, CA; Naval Postgraduate School |
| Description |
The U.S. Army currently stands at an active duty strength of 476,000. MG Joseph Callaway, commander of Personnel Management at Army headquarters, stated recently that the Army missed its recruiting mission and is in danger of not reaching its end strength of 483,500. The Army’s shortfall comes from a strong economy and increased competition from the private sector, which can pay more. The Army is growing its force to meet the high demand for deployments to continue the fight against the war on terrorism. In order to increase its force, the Army must not only recruit new personnel but also ensure that the civilians it recruits complete their first-term obligation contract. This thesis continues the work of Speten in 2018, and uses the Army’s Person-Event Data Environment (PDE) to build a logistic regression model to predict attrition among active duty enlisted soldiers. This research uses demographic and medical factors from the PDE to identify soldiers with the highest probability of failure. We use random forests to identify important predictors of attrition and use those predictors to fit a simple additive logistic regression model. The result shows that PULHES Non-deployable, Dental Class, Contract Duration, Unit Type, Medical Non-deployable, Hearing Class, Gender, Smoker, Education Tier, and Marital Status are the most influential factors that contribute first-term attrition. Subjects: Army; attrition; survival analysis; logistic regression; random forest; enlisted; retention; first-term; classification; predict; tree |
| Language | English |
| Publication date | December 2019 |
| Current location |
IA Collections: navalpostgraduateschoollibrary; fedlink |
| Accession number |
predictingusarmy1094564167 |
| Source | |
| Permission (Reusing this file) |
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States. |
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| current | 21:31, 23 July 2020 |  | 1,275 × 1,650, 74 pages (1.28 MB) | Fæ (talk | contribs) | FEDLINK - United States Federal Collection predictingusarmy1094564167 (User talk:Fæ/IA books#Fork8) (batch 1993-2020 #25063) |
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