The analysis of randomised controlled trial data with more than one follow-up measurement. A comparison between different approaches.
When more than one follow-up measurement is analysed in a randomized controlled trial, there is no consensus how to analyse the overall intervention effect in a proper way. Mostly, longitudinal analysis of covariance is used, because with this method a correction is made for possible regression to the mean. However, in this paper it is shown that this method (mostly) leads to an overestimation of the intervention effect. A possible solution is the use of autoregression, although this does not seem to be the best solution, because it leads to an overcorrection. Due to these flaws, in this paper a new approach is introduced in which a correction for the baseline value is made for the first follow-up, but no correction is made for the remaining follow-up measurements.
Twisk
Jos W R
JW
Department of Methodology and Applied Biostatistics, Institute of Health Sciences, Vrije Universiteit, Amsterdam, The Netherlands. jwr.twisk@vumc.nl
de Vente
Wieke
W
D000704:Analysis of Variance; D003627:Data Interpretation, Statistical; D005500:Follow-Up Studies; D006801:Humans; D016032:Randomized Controlled Trials as Topic / Q000706:statistics & numerical data*; D012044:Regression Analysis