THE EFFECTIVENESS OF ADJUSTMENT BY SUBCLASSIFICATION IN REMOVING BIAS IN OBSERVATIONAL STUDIES.

Abstract

In some investigations, comparison of the means of a variate y in two study groups may be biased because y is related to a variable x whose distribution differs in the two groups. A frequently used device for trying to remove this bias is adjustment by subclassification. The range of x is divided into c subclasses. Weighted means of the subclass means of y are compared, using the same weights for each study group. The effectiveness of this procedure in removing bias depends on several factors, but for monotonic relations between y and x, an analytical approach suggests that for c = 2, 3, 4, 5, and 6 the percentages of bias removed are roughly 64%, 79%, 86%, 90%, and 92%, respectively. The extent to which adjustment reduces the sampling error of the estimated difference between the y means is examined. Under a simple mathematical model, errors of measurement in x reduce the amount of bias removed to a fraction 1/(1+h) of its value, where h is the ratio of the variance of the errors of measurement to the variance of the correct measurements.

Document Details

Document Type
Technical Report
Publication Date
Aug 08, 1967
Accession Number
AD0657849

Entities

People

  • W. G. Cochran

Organizations

  • Harvard University

Tags

DTIC Thesaurus Topics

  • Mathematical Models
  • Measurement
  • Models

Fields of Study

  • Mathematics

Readers

  • Regression Analysis.