Propensity score Joint Estimation Versus 2 stage Estimation #500
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Signed-off-by: Nathaniel <[email protected]>
Signed-off-by: Nathaniel <[email protected]>
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Signed-off-by: Nathaniel <[email protected]>
Signed-off-by: Nathaniel <[email protected]>
Signed-off-by: Nathaniel <[email protected]>
Signed-off-by: Nathaniel <[email protected]>
Signed-off-by: Nathaniel <[email protected]>
Signed-off-by: Nathaniel <[email protected]>
Signed-off-by: Nathaniel <[email protected]>
Signed-off-by: Nathaniel <[email protected]>
Signed-off-by: Nathaniel <[email protected]>
Signed-off-by: Nathaniel <[email protected]>
Signed-off-by: Nathaniel <[email protected]>
Signed-off-by: Nathaniel <[email protected]>
Signed-off-by: Nathaniel <[email protected]>
Signed-off-by: Nathaniel <[email protected]>
NathanielF
changed the title
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View / edit / reply to this conversation on ReviewNB juanitorduz commented on 2025-07-12T08:29:09Z Can you briefly describe what you want to compare, just to keep the storyline flow? |
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View / edit / reply to this conversation on ReviewNB juanitorduz commented on 2025-07-12T08:29:10Z Can you please remove this output ? |
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View / edit / reply to this conversation on ReviewNB juanitorduz commented on 2025-07-12T08:29:11Z @NathanielF Thank you for this simulation! I wanted to do this for years, and this makes everything very clear! |
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View / edit / reply to this conversation on ReviewNB juanitorduz commented on 2025-07-12T08:29:11Z Could you please add an explanation for this section? |
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View / edit / reply to this conversation on ReviewNB juanitorduz commented on 2025-07-12T08:29:12Z Can you please add explanation on what these numbers represent (again, for the non-expert users) |
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View / edit / reply to this conversation on ReviewNB juanitorduz commented on 2025-07-12T08:29:12Z can you please remove this output? |
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View / edit / reply to this conversation on ReviewNB juanitorduz commented on 2025-07-12T08:29:13Z Can you add explanation of this model comparison |
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View / edit / reply to this conversation on ReviewNB juanitorduz commented on 2025-07-12T08:29:13Z Again, can you please add some explanatory test here? |
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View / edit / reply to this conversation on ReviewNB juanitorduz commented on 2025-07-12T08:29:14Z Can you please remove this output? |
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View / edit / reply to this conversation on ReviewNB juanitorduz commented on 2025-07-12T08:29:14Z Can you please remove this output? |
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View / edit / reply to this conversation on ReviewNB juanitorduz commented on 2025-07-12T08:29:15Z can you please add a watemark to get the package versions ? |
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@NathanielF I love these examples 💪 ! Maybe you can ask Andrew Heiss or Jordan Nafa for feedback (maybe once we merge it so that this is not a blocker?) |
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I left some minor comments about adding more explanatory tests is some sections. |
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Thanks @juanitorduz ! Good idea to ask them. Appreciate the quick feedback!!! |
Signed-off-by: Nathaniel <[email protected]>
Signed-off-by: Nathaniel <[email protected]>
Signed-off-by: Nathaniel <[email protected]>
Signed-off-by: Nathaniel <[email protected]>
Signed-off-by: Nathaniel <[email protected]>
Signed-off-by: Nathaniel <[email protected]>
Signed-off-by: Nathaniel <[email protected]>
Working on a draft PR to improve or augment the existing propensity scoring weighting implementation. In particular to make it a bit faster and more "Bayesian". As it currently stands we are performing a two-step strategy where we fit a propensity score model and then push the values of the posterior estimate for the propensity score through a re-weighting routine to estimate the causal contrast.
But we could try and explore a more properly Bayesian model where we fit the propensity score outcome and the model outcome at once in the same model context. This more properly Bayesian and a good bit faster.
See for instance, work here: https://github.com/ajnafa/Latent-Bayesian-MSM by Jordan Nafa and Andrew Heiss
---- EDIT ----
So i think i've finally understood the role of the propensity score in Bayesian estimation and I demonstrate that the two-stage method is what we actually want. The changes i've made are actually quite small. I've added a function to the PyMC model associated with the inverse propensity experiment class.
But in the notebook example i show why this two-stage process is to be preferred over the joint fit model.
📚 Documentation preview 📚: https://causalpy--500.org.readthedocs.build/en/500/