PREDICTING ARMY POST-IET ATTRITION USING LOGISTIC REGRESSION AND TIME-VARYING COVARIATES
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Authors
Cammack, Josephine H.
Subjects
Army
attrition
attrit
post-IET
logistic regression
time-varying covariates
PED
attrition
attrit
post-IET
logistic regression
time-varying covariates
PED
Advisors
Buttrey, Samuel E.
Zhou, Hong
Date of Issue
2020-06
Date
Publisher
Monterey, CA; Naval Postgraduate School
Language
Abstract
The Army is trying to reach a force of 500,000 by 2030. Within the next 10 years, the Army needs to play a balancing act of figuring out how many soldiers will retire, attrit, or not reenlist, and how many will leave for medical or other various reasons. Then the Army needs to figure out how many soldiers need to be recruited every year to reach the 500,000 goal. Because of factors such as lower recruiting goals, tightening labor markets, reduced incentives due to a tighter defense budget, and increasing obesity levels, it is getting harder to recruit prospective soldiers. In such an environment, military leaders need to know why soldiers attrit before their first term is complete, and the factors that contribute to this decision. This thesis uses multiple logistic regressions to determine if a soldier will attrit using personnel data from the Person-Event Data Environment database. We discovered that soldiers who attrit have more variables in common by year in contract than by their contract duration. Thus the models are by year in contract due to the changing nature of time-varying covariates. As the year in contract increases, the effects of demographic indicators generally decrease and the effects of medical-related indicators largely increase. This model can help Army G1 predict how many people will be in the military at a given time—knowledge that will also help leaders determine how to prevent attrition and increase the likelihood of success for soldiers.
Type
Thesis
Description
Series/Report No
Department
Applied Mathematics (MA)
Organization
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NPS Report Number
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Distribution Statement
Approved for public release. distribution is unlimited
Rights
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.