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Causality Confoundingand Control060619

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Causality Confoundingand Control060619

  1. 1. Causality, Confounding, and Control Michel Mouchart, Federica Russo, Guillaume Wunsch Institute of Statistics, UcLouvain Philosophy, University of Kent Institute of Demography, UcLouvain
  2. 2. Overview <ul><li>Models and Structure </li></ul><ul><li>Confounders and Confounding </li></ul><ul><li>Heterogeneity and Latent Confounders </li></ul><ul><li>Controlling Latent Confounders </li></ul><ul><li>Discussion and conclusions </li></ul>
  3. 3. Models and structure (i) <ul><li>What is a statistical model? </li></ul><ul><ul><li>M = { S, P   } </li></ul></ul>Sample space Sampling distribution Parameter <ul><ul><li>A stochastic representation of the world </li></ul></ul><ul><ul><li>Analyze data as a realization of a member of the family of distributions </li></ul></ul>
  4. 4. Models and structure (ii) A S C An example: C ancer, S moking and A sbestos exposure
  5. 5. Models and structure (iii) <ul><li>Each distribution represents </li></ul><ul><li>a data generating process </li></ul><ul><li>The 3 rd component is structural : </li></ul><ul><li>A and S are exogenous variables for  C|A,S </li></ul><ul><li>A and S are causal variables </li></ul>The marginal-conditional decomposition:
  6. 6. Confounders and Confounding <ul><li>C ancer, S moking, A sbestos </li></ul><ul><li>and S ocio- E conomic S tatus </li></ul>A SES S C <ul><li>Standard definitions of confounding: </li></ul><ul><ul><li>A as a confounder </li></ul></ul><ul><li>Confounders as Common cause: </li></ul><ul><ul><li>SES as a confounder </li></ul></ul>
  7. 7. Heterogeneity and Latent Confounders <ul><li>Non observability of confounders: problems for exogeneity </li></ul>SES C S C S A
  8. 8. Controlling Latent Confounders SES K S C A N
  9. 9. To sum up … <ul><li>Exogeneity and confounding are defined only within a structural model </li></ul><ul><li>Exogeneity is relative to parameters of interest </li></ul><ul><li>Confounding as a common cause </li></ul><ul><li>of treatment and outcome </li></ul><ul><li>Latent variables may play havoc with exogeneity </li></ul><ul><li>Controlling for latent variables ? </li></ul>
  10. 10. Conclusions <ul><li>Background knowledge </li></ul><ul><li>is essential in structural modelling </li></ul><ul><li>Meaning of causality: </li></ul><ul><ul><li>epistemic, not metaphysic </li></ul></ul><ul><li>An explicit causalist perspective is justified: </li></ul><ul><ul><li>cognitive and action-oriented goals </li></ul></ul>

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