Data Transformation in Two-Way Analysis of Variance.

Abstract

One purpose of data transformation is to better satisfy the fundamental assumptions of statistical analysis by linear models: (a) Additivity; (b) Homogeneity of variance; (c) Normality. If the original data do not satisfy (a) - (c), a nonlinear transformation may improve approximation to these ideal conditions. This paper considers estimation of the parameter lambda of the family of power transformations, Y(sub T)(Sup lambda) = Y sup lambda if lambda not = 0, Y(Sub T)(Sup lambda) = log Y if lambda = 0 for data conforming to a replicated two-way crossed classification. (Author)

Document Details

Document Type
Technical Report
Publication Date
May 01, 1971
Accession Number
AD0726719

Entities

People

  • James J. Schlesselman

Organizations

  • Educational Testing Service

Tags

DTIC Thesaurus Topics

  • Analysis Of Variance
  • Classification
  • Computing-Related Activities
  • Data Science
  • Homogeneity
  • Information Science
  • Interdisciplinary Science
  • Mathematical Analysis
  • Normality
  • Statistical Analysis

Fields of Study

  • Mathematics

Readers

  • Geospatial Intelligence and Artificial Intelligence Analytics
  • Regression Analysis.