Future Performance Trend Indicators: a Current Value Approach to Human Resources Accounting. Report IV. An Examination and Evaluation of the Statistical Model.

Abstract

This report uses predictive relationships between the Survey of Organizations and measures of organizational effectiveness established in earlier reports (Pecorella and Bowers, 1976a, 1976b, 1977) (AD's A037 733, A033 608, and A036 907), to develop the formal equations, including parameter values, to be used in the value attribution phase. Preliminary to this a series of issues arising from the theoretical and statistical bases of the current value approach are examined. These include: characteristics of variables to be included in the model, assumptions required for prediction of future performance, extension of the univariate methodology to the multivariate case, and the consequences of applying the methodology to this particular data file, for example, standardization of variables and elimination of outliers. A summary of previous and current analyses is also provided. A particular issue is how well the assumptions underlying the multivariate model are met in this particular data file. Analyses show there is no reason to believe the assumptions of multivariate linearity and normality are not met. Other analyses show that one cannot significantly reduce the number of predictor variables in the model. It is concluded that the presented model is appropriate, and the data set is ready to begin the value attribution steps.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1977
Accession Number
ADA045068

Entities

People

  • Alan S. Davenport
  • David G. Bowers
  • Jean B. Lapointe

Organizations

  • University of Michigan

Tags

Communities of Interest

  • Biomedical
  • Human Systems

DTIC Thesaurus Topics

  • Accounting
  • Air Force
  • Business Administration
  • Civilian Personnel
  • Cognition
  • Conductive Polymers
  • Data Sets
  • Human Resources
  • Management Personnel
  • Military Research
  • Models
  • New York
  • Organizational Structure
  • Plastic Explosives
  • Psychology
  • Standards
  • Training

Readers

  • Business Analytics
  • Organizational Psychology.
  • Software Engineering