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Randomized controlled trials (RCTs) in surgery have been impeded by concerns that improvements in the technical performance of a new technique over time (a "learning curve") may distort comparisons. The statistical assessment of learning curves in trials has received little attention. In this paper, we discuss what a learning curve effect is, the factors which effect it, how to display it, and how to incorporate the learning effect into the trial analysis. Bayesian hierarchical models are proposed to adjust the trial results for the existence of a learning curve effect. The implications for trial evaluation and data collection are considered.

Original publication

DOI

10.1191/1740774504cn042oa

Type

Journal article

Journal

Clinical trials (London, England)

Publication Date

01/2004

Volume

1

Pages

421 - 427

Addresses

Health Services Research Unit, University of Aberdeen, Foresterhill, UK. j.a.cook@abdn.ac.uk

Keywords

Humans, Data Interpretation, Statistical, Models, Statistical, Bayes Theorem, Learning, Confounding Factors (Epidemiology), Clinical Competence, Randomized Controlled Trials as Topic, General Surgery