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Article
Propensity score modelling in observational studies using dimension reduction methods
Statistics and Probability Letters, to appear (2011)
  • Debashis Ghosh, Penn State University
Abstract

Conditional independence assumptions are very important in causal inference modelling as well as in dimension reduction methodologies. These are two very strikingly different statistical literatures, and we study links between the two in this article. The concept of covariate sufficiency plays an important role, and we provide theoretical justi cation when dimension reduction and partial least squares methods will allow for valid causal inference to be performed. The methods are illustrated with application to a medical study and to simulated data.

Publication Date
2011
Citation Information
Debashis Ghosh. "Propensity score modelling in observational studies using dimension reduction methods" Statistics and Probability Letters, to appear (2011)
Available at: http://works.bepress.com/debashis_ghosh/49/