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Middle-term Disaggregate Loss Model Test and Evaluation

Middle-term Disaggregate Loss Model Test and Evaluation PDF Author: Allan F. Abrahamse
Publisher:
ISBN:
Category :
Languages : en
Pages : 120

Book Description
"Air Force planners use inventory projection models (IPMs) to predict how an initial inventory of airmen will look in the future. Such IPMs contain loss models that estimate how many members of the initial inventory leave the service during the period in question. Middle-term disaggregate loss models predict annual loss rates, by Air Force Specialty Code (AFSC) and certain other factors. In 1983, as part of a larger effort to develop a new Enlisted Force Management System (EFMS) for the Air Force (Carter et al., 1983), RAND began developing a set of middle-term disaggregate loss models for use in the EFMS's Middle-Term Disaggregate IPM. This document describes the testing and evaluation of these loss models. The purpose of the T & E exercise was to identify problems with the models so that the problems could be fixed before the models were implemented in the EFMS. This document describes the testing and evaluation of a set of equations that predict airman loss and reenlistment behavior. The equations were developed for use in the Air Force's Enlisted Force Management System (EFMS. The conceptual design of the EFMS includes a variety of loss models distinguished by the time horizon of their predictions (short-, middle-, or long-term) and whether such predictions are disaggregated by occupational specialty. This document concerns the middle-term disaggregate loss model, which predicts annual loss rates by Air Force Specialty code (AFSC). Its predictions are designed to be most accurate between one and four years into the future."--DTIC

Middle-term Disaggregate Loss Model Test and Evaluation

Middle-term Disaggregate Loss Model Test and Evaluation PDF Author: Allan F. Abrahamse
Publisher:
ISBN:
Category :
Languages : en
Pages : 120

Book Description
"Air Force planners use inventory projection models (IPMs) to predict how an initial inventory of airmen will look in the future. Such IPMs contain loss models that estimate how many members of the initial inventory leave the service during the period in question. Middle-term disaggregate loss models predict annual loss rates, by Air Force Specialty Code (AFSC) and certain other factors. In 1983, as part of a larger effort to develop a new Enlisted Force Management System (EFMS) for the Air Force (Carter et al., 1983), RAND began developing a set of middle-term disaggregate loss models for use in the EFMS's Middle-Term Disaggregate IPM. This document describes the testing and evaluation of these loss models. The purpose of the T & E exercise was to identify problems with the models so that the problems could be fixed before the models were implemented in the EFMS. This document describes the testing and evaluation of a set of equations that predict airman loss and reenlistment behavior. The equations were developed for use in the Air Force's Enlisted Force Management System (EFMS. The conceptual design of the EFMS includes a variety of loss models distinguished by the time horizon of their predictions (short-, middle-, or long-term) and whether such predictions are disaggregated by occupational specialty. This document concerns the middle-term disaggregate loss model, which predicts annual loss rates by Air Force Specialty code (AFSC). Its predictions are designed to be most accurate between one and four years into the future."--DTIC

Middle-term Loss Prediction Models for the Air Force's Enlisted Force Management System

Middle-term Loss Prediction Models for the Air Force's Enlisted Force Management System PDF Author: Michael P. Murray
Publisher:
ISBN:
Category :
Languages : en
Pages : 84

Book Description
This Note describes procedures for updating the middle-term loss equations that will be used in the Air Force's Enlisted Force Management System (EFMS). Updating involves four activities: (1) adding data to the files used to estimate the equations; (2) reestimating the existing specifications of the equations; (3) exploring possible respecifications of the equations to exploit additional data or to accommodate new EFMS needs; and (4) testing and evaluating new versions of the equations intended for use in the EFMS. This document concentrates on the first three activities. The fourth is treated in N-2688.

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