Accession Number:

ADA025328

Title:

VARSEL: Variable Selection for Multiple-Purpose Prediction Systems in the Absence of External Criteria.

Descriptive Note:

Interim rept. 1 Jan 74-31 Jul 75,

Corporate Author:

AIR FORCE HUMAN RESOURCES LAB BROOKS AFB TEX

Personal Author(s):

Report Date:

1976-05-01

Pagination or Media Count:

16.0

Abstract:

The absence of suitable external criteria for aptitude tests is a recurrent problem for test, battery, and inventory developers in selecting items or tests for inclusion in final operational instruments. This report presents a computing algorithm developed for use when no adequate external selection criterion is available. The algorithm uses a multiple linear regression technique and an accretion variable selection process to start with a large pool of variables and select a minimum subset which can account for the domain of reliable variance measured by all variables in the pool. Two example applications are presented a selection of a subset of tests from a battery of 56 tests and b selection of a subset of job attitude items from a pool of 348 items.

Subject Categories:

  • Psychology
  • Personnel Management and Labor Relations

Distribution Statement:

APPROVED FOR PUBLIC RELEASE