Application of receiver operating characteristic (ROC) methodology in biological studies of marine resourcessex determination of Paracentrotus lividus (Lamarck, 1816)

  1. Lustres Pérez, Vicente
  2. Rodríguez Álvarez, María Xosé
  3. Pata, María P.
  4. Fernández Pulpeiro, Eugenio
  5. Cadarso Suárez, Carmen María
Revista:
Sort: Statistics and Operations Research Transactions

ISSN: 1696-2281

Ano de publicación: 2010

Volume: 34

Número: 2

Páxinas: 239-248

Tipo: Artigo

DIALNET GOOGLE SCHOLAR lock_openAcceso aberto editor

Outras publicacións en: Sort: Statistics and Operations Research Transactions

Resumo

The receiver operating characteristic (ROC) curve is usually used in biomedicine as an indicator of the accuracy of diagnostic tests. However, this measure of discrimination has been little used in other areas, such as animal biology or ecology. We present a novel application of an ROC analysis in which gonad colour was used to determine the sex of Paracentrotus lividus (Lamarck, 1816), a sea urchin of considerable commercial interest. A better classifier than gonad colour was obtained by transforming these colours through flexible logistic generalized additive models.

Referencias bibliográficas

  • Catoira, J. L. (1995). Spatial and temporal evolution of thegonad index of the sea urchinParacentrotus lividus (Lamarck) in Galicia, Spain. In: Emson, R., Smith, A. and Campbell, A. (eds.).Echinoderm Research. Balkema, Rotterdam, 295-298.
  • Crapp, G. B. and Willis, M. E. (1975). Age determination in the sea urchinParacentrotus lividus(Lamarck), with notes on the reproductive cycle.Journal of Experimental Marine Biology and Ecology, 20, 157- 178.
  • Efron, B. and Tibshirani, R. J. (1993).An Introduction to the Bootstrap. Chapman & Hall/CRP Press, New York.
  • Eilers, P. and Marx, B. (1996). Flexible smoothing with B-splines and penalties.Statistical Science, 11, 89- 121.
  • Hanley, J. A. and McNeil, B. J. (1982). The meaning and use of the area under a receiver operating characteristic (ROC) curve.Radiology, 143, 29-36.
  • Hastie, T. J and Tibshirani, R. J. (1990).Generalized Additive Models. Chapman & Hall, London.
  • Lang, S. and Brezger, A. (2004). Bayesian P-splines.Journal of Computational and Graphical Statistics, 13, 183-212.
  • Lustres-Ṕerez, V. (2006). El erizo de mar:Paracentrotus lividus(Lamarck, 1816) en las costas de Galicia. PhD thesis. Universidad de Santiago de Compostela.
  • McIntosh, M. W. and Pepe, M. S. (2002). Combining several screening tests: optimality of the risk score. Biometrics, 58, 657-664.
  • McCullagh, P. and Nelder, J. (1989).Generalized Linear Models. Second Edition. Chapman and Hall, London.
  • Metz, C. E. (1978). Basic principles of ROC analysis.Seminars in Nuclear Medicine, 8, 283-298.
  • Monteiro-Torreiro, M. F. and Garcia-Martinez, P. (2003). Seasonal changes in the biochemical composition of body components of the sea urchin,Paracentrotus lividus, in Lorbé (Galicia-north-western Spain). Journal of the Marine Biological Association of the United Kingdom, 83, 575-581.
  • Neyman, J. and Pearson, E. S. (1933). On the problem of the most efficient tests of statistical hypothesis. Philosophical Transactions of the Royal Society of London,Series A, 231, 289-337.
  • Sellem, F. and Guillou, M. (2007). Reproductive biology ofParacentrotus lividus(Echinodermata: Echinoidea) in two contrasting habitats of northern Tunisia (south-east Mediterranean).Journal of the Marine Biological Association of the United Kingdom, 87, 763-767.
  • Shpigel, M., McBride, S. C., Marciano, S., Ron, S. and Ben-Amotz, A. (2005). Improving gonad colour and somatic index in the European sea urchinParacentrotus lividus. Aquaculture, 245, 101-109.
  • Shpigel, M., Schlosser, S. C., Ben-Amotz, A., Lawrence, A. L. and Lawrence, J. M. (2006). Effects of dietary carotenoid on the gut and the gonad of the sea urchinParacentrotus lividus. Aquaculture, 261, 1269-1280.
  • Sing, T., Sander, O., Beerenwinkel, N. and Lengauer, T. (2005). ROCR: visualizing classifier performance in R. Bioinformatics, 21(20), 3940-3941.
  • Swets, J. A. and Pickett, R. M. (1982).Evaluation of Diagnostic Systems: Methods from Signal Detection Theory. Academic Press, New York.
  • Tortonese, E. (1965).Fauna d’Italia. Echinodermata. Calderini, Bologna.
  • Wand, M. P. and Jones, M. C. (1995).Kernel Smoothing, Chapman & Hall, London.
  • Wood, S. N. (2003). Thin plate regression splines.Journal of the Royal Statistical Society: Series B65, 95-114.
  • Wood, S. N. (2004). Stable and efficient multiple smoothing parameter estimation for generalized additive models.Journal of the American Statistical Association, 99, 673-686.
  • Wood, S. N. (2006).Generalized Additive Models, An Introduction with R. Chapman & Hall/CRC, Boca Raton, Florida.
  • Xunta de Galicia. Plataforma tecnolóxica da pesca. Consellerı́a do mar. http://www.pescadegalicia.com/default.htm (accessed: 23 November, 2010).
Fonte de datos: Dialnet