Some Differences Between Fixed, Mixed, and Random Effects Analysis of Variance Models

Article

Feder, Paul I.   (1974, ASQC)   General Electric Company, Schenectady, NY

Journal of Quality Technology    Vol. 6    No. 2
QICID: 5163    April 1974    pp. 98-106
List $10.00
Member $5.00

FOR A LIMITED TIME, ACCESS TO THIS CONTENT IS FREE!
You will need to be signed in.
New to ASQ? Register here.

Article Abstract

The analysis of variance is a technique for comparing treatment means or for estimating components of variation. The former is called fixed effects analysis of variance and the latter is called random effects analysis of variance. Many nonstatisticians who use canned analysis-of-variance computer programs do not appreciate this difference and incorrectly perform a fixed effects analysis when a random effects analysis is needed. The same set of data can lead to opposite conclusions, depending on whether a fixed or random effects analysis is appropriate. This article discusses differences in the assumptions, analyses, and inferences for fixed and random effects analysis of variance models. The mixed effects model, which is a combination of the fixed and random effects models, is also briefly described. The main message is that not all analysis of variance models are fixed effects models and that random effects require different treatment from fixed effects. The entire discussion is illustrated by practical examples.

Keywords

Fixed-effects model,Random effects,Statistical methods


Browse QIC Articles Chronologically:     Previous Article     Next Article

New Search

Featured advertisers





ASQ is a global community of people passionate about quality, who use the tools, their ideas and expertise to make our world work better. ASQ: The Global Voice of Quality.