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.

• Publication year

  2008

• Venue

  European Journal of Epidemiology

• Publication date

  2008-08-19

• Fields of study

  Mathematics, Medicine

• Identifiers
  DOI 10.1007/s10654-008-9279-6PMID 18712484
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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