Symptoms, signs and statistics: Statistics applied to the health and life sciences

Authors

  • Miguel A. Martínez-Beneito Foundation for the Promotion of Health and Biomedical Research in Valencia, Spain (FISABIO).
  • José D. Bermúdez University of Valencia (Spain).
  • Carmen Armero University of Valencia (Spain).

DOI:

https://doi.org/10.7203/metode.0.3828

Keywords:

biostatistics, health and life sciences, clinical trials, epidemiology, survival

Abstract

Experimental determination or detection of the physiological mechanisms underlying disease is by and large a highly complex task. This fact has turned epidemiology into the main tool for generating knowledge in the medical field. Epidemiology studies diseases by monitoring the health of groups of people, rather than through individual observations. If the primary tool for generating medical knowledge is based on the observation of groups of people (population samples) from which we wish to learn (make inferences), then the link between statistics and medicine is clear. Here we illustrate this nexus presenting three statistical research areas that are particularly valuable for biomedical research.

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Author Biographies

Miguel A. Martínez-Beneito, Foundation for the Promotion of Health and Biomedical Research in Valencia, Spain (FISABIO).

Researcher at the Foundation for the Promotion of Health and Biomedical Research in Valencia (FISABIO). Member of CIBER of Epidemiology and Public Health (CIBERESP) and the National Network for Biostatistics Biostatnet.  

José D. Bermúdez, University of Valencia (Spain).

Professor at the Department of Statistics and Operations Research. University of Valencia (Spain). Member of the National Network for Biostatistics Biostatnet.

Carmen Armero, University of Valencia (Spain).

Professor at the Department of Statistics and Operations Research. University of Valencia (Spain). Member of the National Network for Biostatistics Biostatnet.

References

Aalen, O. O.; Borgan, Ø. and H. K. Gjessing, 2008. Survival and Event History Analysis: A Process Point of View. Springer. New York.

Besag, J.; York, J. and A. Mollié, 1991. «Bayesian Image Restoration, with Two Applications in Spatial Statistics». Annals of the Institute of Statistical Mathematics, 43(1): 1-20. DOI: <10.1007/BF00116466>.

Cook, T. D. and D. L. DeMets, 2008. Introduction to Statistical Methods for Clinical Trials. Chapman & Hall/CRC. Boca Raton, USA.

Diggle, P. J.; Heagerty, P. J.; Liang, K.-Y. and S. Zeger, 2002. Analysis of Longitudinal Data. Oxford University Press.

Oxford. Holland, P. W., 1986. «Statistics and Causal Inference». Journal of the American Statistical Association, 81(396): 945-960. DOI: <10.2307/2289064>.

Matthews, J. N. S., 2006. Introduction to Randomized Controlled Clinical Trials. Chapman & Hall/CRC. Boca Raton, USA.

Rubin, D. B., 1974. «Estimating Causal Effects of Treatments in Randomized and Non-Randomized Studies». Journal of Educational Psychology, 66 (5): 688-701. DOI: <10.1037/h0037350>.

Published

2015-04-16

How to Cite

Martínez-Beneito, M. A., Bermúdez, J. D., & Armero, C. (2015). Symptoms, signs and statistics: Statistics applied to the health and life sciences. Metode Science Studies Journal, (5), 151–157. https://doi.org/10.7203/metode.0.3828
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Section

The digits of science. Statistics as scientific tool

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