Arbeitspapier

Bayesian Exploratory Factor Analysis

This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor, and the corresponding factor loadings. Classical identification criteria are applied and integrated into our Bayesian procedure to generate models that are stable and clearly interpretable. A Monte Carlo study confirms the validity of the approach. The method is used to produce interpretable low dimensional aggregates from a high dimensional set of psychological measurements.

Sprache
Englisch

Erschienen in
Series: IZA Discussion Papers ; No. 8338

Klassifikation
Wirtschaft
Bayesian Analysis: General
Multiple or Simultaneous Equation Models: Classification Methods; Cluster Analysis; Principal Components; Factor Models
Computational Techniques; Simulation Modeling
Thema
Bayesian factor models
exploratory factor analysis
identifiability
marginal data augmentation
model expansion
model selection

Ereignis
Geistige Schöpfung
(wer)
Conti, Gabriella
Frühwirth-Schnatter, Sylvia
Heckman, James J.
Piatek, Rémi
Ereignis
Veröffentlichung
(wer)
Institute for the Study of Labor (IZA)
(wo)
Bonn
(wann)
2014

Handle
Letzte Aktualisierung
2025-03-10T11:42:47+0100

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Conti, Gabriella
  • Frühwirth-Schnatter, Sylvia
  • Heckman, James J.
  • Piatek, Rémi
  • Institute for the Study of Labor (IZA)

Entstanden

  • 2014

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