Abstract
Principal stratification is an increasingly adopted framework for drawing counterfactual causal inferences in complex situations. After outlining the framework, with special emphasis on the case of truncation by death, I describe an application of the methodology where the analysis is based on a parametric model with latent classes. Then, I discuss the special features of latent class models derived within the principal strata framework. I argue that the concept of principal stratification gives latent class models a solid theoretical basis and helps to solve some specification and fitting issues.
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Grilli, L. (2011). Causal Inference Through Principal Stratification: A Special Type of Latent Class Modelling. In: Fichet, B., Piccolo, D., Verde, R., Vichi, M. (eds) Classification and Multivariate Analysis for Complex Data Structures. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13312-1_27
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DOI: https://doi.org/10.1007/978-3-642-13312-1_27
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