Using the PISE Criterion to Measure the Effects of Imbalance in the Analysis of Covariance

Abstract

This Note describes a new statistical technique for comparing unbalanced experimental designs which will be modeled by the univariate analysis of covariance. We propose minimizing a design criterion variable called PISE (percent inflation of the standard error of a contrast). The research was motivated by the need to design an experiment to measure the effectiveness of a potential new Army recruitment policy. The policy would provide greater management flexibility in paying cash bonuses to eligible "high-quality" young men who agree to enlist in the U.S. Army. We provide results for both the standard Gauss-Markov model (constant error variance) and the model with heteroscedasticity. We also discuss the problem of attributing the increased variance caused by imbalance in a design to particular covariates. When implemented, the proposed PISE criterion will generate a design which has greater sensitivity to treatment effect differences.

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 1983
Accession Number
ADA596209

Entities

People

  • S. J. Press

Organizations

  • RAND Corporation

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Analysis Of Variance
  • Business Administration
  • Contrast
  • Corporations
  • Covariance
  • Data Science
  • Experimental Data
  • Experimental Design
  • Information Science
  • Knowledge Management
  • Markov Models
  • Recruiting
  • Statistical Algorithms
  • Statistical Analysis
  • Statistics
  • Surveys
  • United States

Fields of Study

  • Mathematics

Readers

  • Naval Personnel Management
  • Statistical inference.
  • Systems Analysis and Design