An Algorithm for the Univariate Analysis of Variance in Experiments with Repeated Measures.

Abstract

A computing procedure is described for the univariate analysis of a repeated measurements experiment where the experimental units (frequently subjects) are arranged in a two-way classification with cell frequencies that can be disproportionate. The analysis is adjusted for missing values, provided their number and configuration do not violate certain limitations. Unlike some strategies for handling missing values in repeated measurements experiments, the method does not require the inclusion in the model of an explicit subject factor, meaning that the order of the matrix to be inverted does not depend on the number of subjects in the experiment. The algorithm has been incorporated into a SAS procedure, REP2W1F, which computes the full analysis with a single call and produces useful summary statistics (including least-squares means) particular to the design. The approach could be generalized to experiments where the number of treatment factors is other than two and where the repeated measures that a factorial arrangement of their own.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1982
Accession Number
ADA125380

Entities

People

  • Richard C. Mcnee
  • William G. Jackson Jr.

Organizations

  • United States Air Force School of Aerospace Medicine

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Aerospace Medicine
  • Air Force
  • Air Force Facilities
  • Algorithms
  • Analysis Of Variance
  • Cell Size
  • Central Processing Units
  • Classification
  • Computer Programs
  • Computers
  • Core Storage
  • Data Science
  • Equations
  • Information Science
  • Measurement
  • Statistics
  • Subject Indexing

Readers

  • Computer Science.
  • Regression Analysis.