Methods for assessing difference between groups in change when initial measurement is subject to intra‐individual variation
- 1 January 1993
- journal article
- clinical trial
- Published by Wiley in Statistics in Medicine
- Vol. 12 (13), 1213-1237
- https://doi.org/10.1002/sim.4780121304
Abstract
Statistical analysis of difference between groups in change for some variable, adjusting for initial value, is complicated by the presence of intra‐individual variation in that variable. We estimate here the asymptotic bais that results from calculating the adjusted between‐group difference by ordinary least squares (OLS) from observed data. We also present explicit formulae that use the OLS estimates, the difference between treatment groups in mean initial values, and a measure of the intra‐individual variation to compute a corrected estimator and its variance. Alternatively, we can use OLS on transformed data to obtain unbiased estimates, in which we replace initial observed values by conditional Stein estimates of true values. We illustrate the results with data from an observational study and a clinical trial.Keywords
This publication has 20 references indexed in Scilit:
- Short-term intraindividual variability in hemostasis factors the ARIC studyAnnals of Epidemiology, 1992
- Errors-in-Variables Regression Using Stein EstimatesThe American Statistician, 1989
- Covariate imbalance and random allocation in clinical trialsStatistics in Medicine, 1989
- Covariate measurement error in generalized linear modelsBiometrika, 1987
- Regression Estimation after Correcting for AttenuationJournal of the American Statistical Association, 1978
- On the Relation Between Change and Initial ValueJournal of the American Statistical Association, 1977
- Some effects of within-person variability in epidemiological studiesJournal of Chronic Diseases, 1973
- Serum cholesterol changes: Effects of diet and regression toward the meanJournal of Chronic Diseases, 1972
- Errors of Measurement in StatisticsTechnometrics, 1968
- Asymptotic Normality and Consistency of the Least Squares Estimators for Families of Linear RegressionsThe Annals of Mathematical Statistics, 1963