Lozano Bleda, Jose Hector joseh.lozano@uam.es

Publications

Investigating operation-specific learning effects in the Raven's Advanced Progressive Matrices: A linear logistic test modeling approach

  • Lozano JH
  • Revuelta J

Intelligence - 1/9/2020

10.1016/j.intell.2020.101468 View at source

  • ISSN 01602896

Bayesian Estimation and Testing of a Linear Logistic Test Model for Learning during the Test

  • Lozano, Jose H.
  • Revuelta, Javier;

Applied Measurement In Education (p. 223-235) - 30/7/2021

10.1080/08957347.2021.1933982 View at source

  • ISSN 15324818

A Bayesian Generalized Explanatory Item Response Model to Account for Learning During the Test

  • Lozano, Jose H.
  • Revuelta, Javier;

Psychometrika (p. 994-1015) - 30/8/2021

10.1007/s11336-021-09786-x View at source

  • ISSN 00333123

A Bayesian General Model to Account for Individual Differences in Operation-Specific Learning Within a Test

  • Lozano JH
  • Revuelta J

Educational And Psychological Measurement (p. NULL-807) - 1/1/2022

10.1177/00131644221109796 View at source

  • ISSN 00131644

This researcher has no books.

This researcher has no book chapters.

Bayesian estimation of item response models to account for learning during the test

  • Lozano, J. H., & Revuelta, J

25/7/2018

  • iMarina

This researcher has no working papers.

This researcher has no technical reports.

Análisis bayesiano psicométrico de ítems de elección forzosa con respuesta continua mediante la distribución DIRICHLET

  • Lozano Bleda, Jose Hector (Colaborador/a)
  • Ximenez Gomez, Maria Carmen (Investigador principal (IP))
  • Revuelta Menendez, Javier (Investigador principal (IP))

Period: 01-01-2019 - 30-09-2022

Type of funding: National

Amount of funding: 36300,00 Euros.

  • iMarina

ANÁLISIS FACTORIAL BAYESIANO DE ÍTEMS DE ELECCIÓN FORZOSA

  • Martín Fernández, Manuel (Colaborador/a)
  • Lozano Bleda, Jose Hector (Colaborador/a)
  • Revuelta Menendez, Javier (Investigador principal (IP))
  • Ximenez Gomez, Maria Carmen (Investigador principal (IP))

Period: 01-09-2022 - 31-08-2026

Type of funding: National

Amount of funding: 50578,00 Euros.

  • iMarina

This researcher has no supervised thesis.

This researcher has no patents or software licenses.

Last data update: 8/12/23 1:17 AM