Percentiles curves based on multivariate conditional transformation models.Application to diabetes

  1. Óscar Lado Baleato
  2. Carmen María Cadarso Suárez
  3. Thomas Kneib
  4. Francisco Gude Sampedro
Libro:
Proceedings of the 35th International Workshop on Statistical Modelling : July 20-24, 2020 Bilbao, Basque Country, Spain
  1. Itziar Irigoien (ed. lit.)
  2. Dae-Jin Lee (ed. lit.)
  3. Joaquín Martínez-Minaya (ed. lit.)
  4. María Xosé Rodríguez- Álvarez (ed. lit.)

Editorial: Servicio Editorial = Argitalpen Zerbitzua ; Universidad del País Vasco = Euskal Herriko Unibertsitatea

ISBN: 978-84-1319-267-3

Año de publicación: 2020

Páginas: 137-141

Congreso: International Workshop on Statistical Modelling (35. 2020. Bilbao)

Tipo: Aportación congreso

Objetivos de desarrollo sostenible

Resumen

Multivariate Conditional Transformation Models (MCTMs) were recently proposed as a new multivariate regression technique. MCTMs characterize jointly the covariates e ects on the marginal distributions of the responses and their correlations. Flexibility, in both the responses and covariates e ects are achieved using Bernstein polynomial basis. Based on MCTMs, in this paper percentile curves are constructed for each response. Simulation studies indicated the good performance of these estimated condtional percentiles. Finally, MCTMs percentile curves were obtained for three diabetes markers (fasting plasma glucose, glycated hemoglobin and fructosamine) condtionally on age.