An Investigation of the Effects of Rank, AFSC, and Dependents on the Length of the Separation for Air Force Enlisted Join Spouse Couples.

Abstract

The purpose of this thesis was to perform a statistical analysis of the effects of rank, AFSC and dependents on the lengths of separation (LOS) experienced by Air Force enlisted couples when one or both of them are reassigned. Data on enlisted couples was gathered from the permanent universal air-men records, maintained by the Air Force Human Resources Laboratory. This data contained assignment, dependent, and AFSC information on enlisted members married to another enlisted member during the years 1980 through 1985. Additional information from the Rapid Access Personnel Survey (RAPS) on join spouse matters was obtained from the Air Force Military Personnel Center. The statistical analysis resulted in determining that the mean LOS for all enlisted join spouse couples who were reassigned over the last six years was 3.1 months. There was also a difference in the mean LOS for each rank with the higher mean LOS for those in the ranks of E-2 and E-3. It was also determined that the rate of assignment rejection was dependent on the length of the separation and the reenlistment status of the individual. In addition, those with a stated intention of remaining in the Air Force for at least 20 years were more likely to accept assignments involving a family separation than were those who had not decided to make the Air Force a career.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1985
Accession Number
ADA167125

Entities

People

  • Maureen R. Harrington

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Air Force
  • Air Force Personnel
  • Computer Programming
  • Computers
  • Data Science
  • Databases
  • Enlisted Personnel
  • Experimental Design
  • Information Processing
  • Information Science
  • Knowledge Management
  • Military Personnel
  • Probability
  • Statistical Algorithms
  • Statistical Analysis
  • Surveys
  • United States

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