Intervention and Identifiability in Latent Variable Modelling

Jan-Willem Romeijn*, Jon Williamson

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

We consider the use of interventions for resolving a problem of unidentified statistical models. The leading examples are from latent variable modelling, an influential statistical tool in the social sciences. We first explain the problem of statistical identifiability and contrast it with the identifiability of causal models. We then draw a parallel between the latent variable models and Bayesian networks with hidden nodes. This allows us to clarify the use of interventions for dealing with unidentified statistical models. We end by discussing the philosophical and methodological import of our result.

Original languageEnglish
Pages (from-to)243-264
Number of pages22
JournalMinds and machines
Volume28
Issue number2
DOIs
Publication statusPublished - Jun-2018

Keywords

  • Interventions
  • Statistical inference
  • Identifiability
  • Latent variable modelling
  • FACTOR-INDETERMINACY

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