Differentially Weighting Linear Models of Behavior: An Empirical Comparison of Six Methods.

Abstract

Six methods of estimating regression weights for a linear model of behavior were compared in 51 samples of National Guardsmen. Ordinary least squares, Bayesian m-group regression, ridge regression, equal weighting, and two related methods were used. Weights were estimated in one-half of each sample and then applied to data in the other half. Ratios of observations to predictors ranged from 4:1 to 19:1. Cross validation R sq was used as the index of model or equation stability. Results support earlier findings that least squares weights are relatively unstable in small samples, but do not indicate the superiority of any one other method. Future research and implications for using these regression techniques in testing behavioral models are discussed. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1980
Accession Number
ADA086876

Entities

People

  • Charles K. Parsons
  • Charles L. Hulin

Organizations

  • University of Illinois Urbana–Champaign

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Applied Psychology
  • Coefficients
  • Computational Science
  • Covariance
  • Data Science
  • Equations
  • Errors
  • Experimental Data
  • Human Behavior
  • Military Research
  • National Guard
  • Plastic Explosives
  • Psychology
  • Sampling
  • Standards
  • Supervisors
  • Universities

Fields of Study

  • Psychology

Readers

  • Regression Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference