publication . Other literature type . Article . 2014

Linear mixed-effects models for central statistical monitoring of multicenter clinical trials.

Marc Buyse;
  • Published: 01 Jan 2014
  • Publisher: Wiley
  • Country: Belgium
Abstract
Multicenter studies are widely used to meet accrual targets in clinical trials. Clinical data monitoring is required to ensure the quality and validity of the data gathered across centers. One approach to this end is central statistical monitoring, which aims at detecting atypical patterns in the data by means of statistical methods. In this context, we consider the simple case of a continuous variable, and we propose a detection procedure based on a linear mixed-effects model to detect location differences between each center and all other centers. We describe the performance of the procedure as a function of contamination rate and signal-to-noise ratio. We inv...
Subjects
free text keywords: multicenter clinical trial, error detection, linear mixed-effects model, Error detection and correction, Accrual, Statistical monitoring, Signal-to-noise ratio, Continuous variable, Clinical trial, Data mining, computer.software_genre, computer, Contamination rate, Econometrics, Data monitoring, Computer science, Statistics, multicenter clinical trial; statistical monitoring; error detection; contamination rate; signal-to-noise ratio; linear mixed-effects model
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publication . Other literature type . Article . 2014

Linear mixed-effects models for central statistical monitoring of multicenter clinical trials.

Marc Buyse;