Middle-Term Disaggregate Loss Model Test and Evaluation: Description and Results

Abstract

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. Keywords: Reenlistment, Attrition, Mathematical models, Forecasting.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1988
Accession Number
ADA197857

Entities

People

  • Allan F. Abrahamse

Organizations

  • RAND Corporation

Tags

DTIC Thesaurus Topics

  • Air Force
  • Air Force Personnel
  • Blending
  • Corporations
  • Enlisted Personnel
  • Equations
  • Inventory
  • Management Personnel
  • Mathematical Models
  • Personnel Management
  • Probability
  • Random Variables
  • Recruiting
  • Reenlistment
  • Specifications
  • Standards
  • Test And Evaluation

Readers

  • Computational Modeling and Simulation
  • Military Mobilization and Reserve Forces Studies.
  • Occupational Health and Safety.