Methods for assessing difference between groups in change when initial measurements is subject to intra-individual variation.

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 bias 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.