Column: Statistics Roundtable: One Way To Moderate Ceiling Effects

Article

Gunst, Richard F; Barry, Thomas E   (2003, ASQ)   Southern Methodist University in Dallas

Quality Progress    Vol. 36    No. 10
QICID: 19228    October 2003    pp. 84-86
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Article Abstract

Multiple linear regression models are ordinarily defined with a continuous (usually normally distributed) response variable. In many applications of regression modeling, however, the response variable is constrained by fixed, achievable lower and upper bounds. With such data, ceiling effects can cause a number of difficulties when interpreting the fit and drawing inferences.

Keywords

Interactions, Regression modeling, Response variables


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