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Conditions for Non‐confounding and Collapsibility without Knowledge of Completely Constructed Causal Diagrams

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  • ZHI GENG
  • GUANGWEI LI

Abstract

In this paper, we discuss several concepts in causal inference in terms of causal diagrams proposed by Pearl (1993, 1995a, b), and we give conditions for non‐confounding, homogeneity and collapsibility for causal effects without knowledge of a completely constructed causal diagram. We first introduce the concepts of non‐confounding, conditional non‐confounding, uniform non‐confounding, homogeneity, collapsibility and strong collapsibility for causal effects, then we present necessary and sufficient conditions for uniform non‐confounding, homegeneity and collapsibilities, and finally we show sufficient conditions for non‐confounding, conditional non‐confounding and uniform non‐confounding.

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  • Zhi Geng & Guangwei Li, 2002. "Conditions for Non‐confounding and Collapsibility without Knowledge of Completely Constructed Causal Diagrams," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 29(1), pages 169-181, March.
    • Handle: RePEc:bla:scjsta:v:29:y:2002:i:1:p:169-181
    DOI: 10.1111/1467-9469.00087
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    Cited by:

    1. Pekka Kekolahti & Juuso Karikoski & Antti Riikonen, 2015. "The effect of an individual’s age on the perceived importance and usage intensity of communications services—A Bayesian Network analysis," Information Systems Frontiers, Springer, vol. 17(6), pages 1313-1333, December.

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