Effect of regression to the mean in multivariate distributions
- 1 January 1992
- journal article
- research article
- Published by Taylor & Francis in Communications in Statistics - Theory and Methods
- Vol. 21 (2) , 333-350
- https://doi.org/10.1080/03610929208830782
Abstract
Estimating treatment effects in the presence of regression to the mean is a problem arising in truncated distributions that is being recognized with increasing interest in recent literature. As noted in a previous communication by the authors (1991), any extraneous source of variability such as within-subject variability and measurement errors can contribute to the magnitude of regression toward the mean. The main focus of this paper is consideration of a model for estimating treatment effects when truncation and regression to the mean occur on more than one random variable. This situation occurs often in investigations where subjects are selected for study because measurements on two characteristics of interest both exceed specified values.Keywords
This publication has 16 references indexed in Scilit:
- Effect of regression to the mean in the presence of within‐subject variabilityStatistics in Medicine, 1991
- Regression Toward the Mean and the Paired Sample t TestThe American Statistician, 1991
- Regression: A New Mode for an Old Meaning?The American Statistician, 1990
- Generalized modulus power transformationsCommunications in Statistics - Theory and Methods, 1988
- Regression to the modeStatistica Neerlandica, 1983
- Stein's Paradox in StatisticsScientific American, 1977
- THE EFFECT OF REGRESSION TO THE MEAN IN EPIDEMIOLOGIC AND CLINICAL STUDIESAmerican Journal of Epidemiology, 1976
- Some effects of within-person variability in epidemiological studiesJournal of Chronic Diseases, 1973
- Stein's Estimation Rule and Its Competitors--An Empirical Bayes ApproachJournal of the American Statistical Association, 1973
- Serum cholesterol changes: Effects of diet and regression toward the meanJournal of Chronic Diseases, 1972