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A generalised Box--Cox transformation for the parametric estimation of clinical reference intervals

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  • Jonathan Gillard

Abstract

Parametric methods for the calculation of reference intervals in clinical studies often rely on the identification of a suitable transformation so that the transformed data can be assumed to be drawn from a Gaussian distribution. In this paper, the two-stage transformation recommended by the International Federation for Clinical Chemistry is compared with a novel generalised Box--Cox family of transformations. Investigation is also made of sample sizes needed to achieve certain criteria of reliability in the calculated reference interval. Simulations are used to show that the generalised Box--Cox family achieves a lower bias than the two-stage transformation. It was found that there is a possibility that the two-stage transformation will result in percentile estimates that cannot be back-transformed to obtain the required reference intervals, a difficulty not observed when using the generalised Box--Cox family introduced in this paper.

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  • Jonathan Gillard, 2012. "A generalised Box--Cox transformation for the parametric estimation of clinical reference intervals," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(10), pages 2231-2245, June.
    • Handle: RePEc:taf:japsta:v:39:y:2012:i:10:p:2231-2245
    DOI: 10.1080/02664763.2012.706266
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    Cited by:

    1. Santiago Cajiao Raigosa & Luis Fernando Melo Velandia & Daniel Parra Amado, 2014. "Pronósticos para una economía menos volátil: el caso colombiano," Coyuntura Económica, Fedesarrollo, December.
    2. Santiago Cajiao Raigosa & Luis Fernando Melo Velandia & Daniel Parra Amado, 2014. "Pronósticos para una economía menos volátil: El caso colombiano," Borradores de Economia 11252, Banco de la Republica.

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