Una pequeña mirada a la estadística bayesiana en el análisis de datos cardiológicos

• Carmen Armero Cervera ^[1] ; Patricia Rodríguez Pérez ^[3] ; José M. de la Torre Hernández ^[2]
  1. [1] Universitat de València

     Universitat de València

     Valencia, España

     
  2. [2] Hospital Universitario Marqués de Valdecilla

     Hospital Universitario Marqués de Valdecilla

     Santander, España

     
  3. [3] Clinical and Medical Affairs Department, Biotronik Spain, España

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• Localización: REC: Interventional Cardiology, ISSN-e 2604-7276, ISSN 2604-7306, Vol. 4, Nº. 3, 2022, págs. 207-215
• Idioma: español
• DOI: 10.24875/RECIC.M22000284
• Títulos paralelos:
  • A brief look into Bayesian statistics in cardiology data analysis
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• Dialnet Métricas: 1 Cita
• Resumen
  • español

    La estadística bayesiana valora de forma probabilística cualquier fuente de incertidumbre asociada a un estudio estadístico y utiliza el teorema de Bayes para actualizar, de manera secuencial, la información generada en las diferentes fases del estudio. Las características de la inferencia bayesiana la hacen especialmente útil para el tratamiento de datos cardiológicos procedentes de estudios experimentales u observacionales que contienen diferentes fuentes de variabilidad y complejidad. En este trabajo se presentan los conceptos básicos de la estadística bayesiana relativos a la estimación de parámetros y cantidades derivadas, predicción de nuevos datos y contrastes de hipótesis; estos últimos en el contexto de la selección de modelos o teorías.

  • English

    Bayesian statistics assesses probabilistically all sources of uncertainty involved in a statistical study and uses Bayes’ theorem to sequentially update the information generated in the different phases of the study. The characteristics of Bayesian inference make it particularly useful for the treatment of cardiological data from experimental or observational studies including different sources of variability, and complexity. This paper presents the basic concepts of Bayesian statistics associated with the estimation of parameters and derived quantities, new data prediction, and hypothesis testing. The latter in the context of model or theory selection.

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