[DiogoRibeiro7]

Continues the assumption-focused causal-inference layer.

What changed

• adds 04-causal-inference/transportability-external-validity/;
• adds the canonical presentation/main.tex entry point;
• adds Transportability and External Validity;
• covers internal vs external validity, source and target populations, effect modification, standardization, transport weighting, support, covariate shift, site heterogeneity, trial-to-target generalization, temporal drift, treatment-version differences, and sensitivity to unmeasured effect modifiers;
• registers the deck in the presentation contract validator;
• registers the deck in GitHub Actions and compile_all.sh;
• updates the causal-inference domain index.

Review note

This PR intentionally does not merge automatically.

---

Summary by cubic

Adds a new lecture deck on transportability and external validity to the causal-inference layer, covering when causal effects estimated in one population, site, or time period can be applied to another.

This PR intentionally does not merge automatically.

• Adds the 04-causal-inference/transportability-external-validity/ topic with README, main.tex entry point, and the 33-slide beamer lecture.
• Registers the deck in GitHub Actions, compile_all.sh, the presentation contract validator, and the causal-inference domain index.

^{Written for commit ff7c647. Summary will update on new commits.}

[cubic-dev-ai]

2 issues found across 7 files

Prompt for AI agents (unresolved issues)

Check if these issues are valid — if so, understand the root cause of each and fix them. When an issue isn't valid or won't be fixed in this PR, reply in its thread with the reason and then resolve the thread. If appropriate, use sub-agents to investigate and fix each issue separately.


<file name="04-causal-inference/transportability-external-validity/presentation/transportability_external_validity_beamer.tex">

<violation number="1" location="04-causal-inference/transportability-external-validity/presentation/transportability_external_validity_beamer.tex:108">
P2: This average identifies the target ATE only if the conditional effect is invariant between study and target given `X`. State that cross-population assumption here; measuring modifiers alone does not establish it.</violation>

<violation number="2" location="04-causal-inference/transportability-external-validity/presentation/transportability_external_validity_beamer.tex:323">
P3: The Dahabreh et al. reference gives the wrong year and volume: the article appeared in Biometrics 75(2), June 2019, pages 685–694 (doi:10.1111/biom.13009), not 2020, 76(2). Update year and volume/issue so readers can locate the correct source.</violation>
</file>

<sub>Reply with feedback, questions, or to request a fix.

Re-trigger cubic</sub>

[cubic-dev-ai]

P2: This average identifies the target ATE only if the conditional effect is invariant between study and target given X. State that cross-population assumption here; measuring modifiers alone does not establish it.

Prompt for AI agents

Check if this issue is valid — if so, understand the root cause and fix it. When an issue isn't valid or won't be fixed in this PR, reply in its thread with the reason and then resolve the thread. At 04-causal-inference/transportability-external-validity/presentation/transportability_external_validity_beamer.tex, line 108:

<comment>This average identifies the target ATE only if the conditional effect is invariant between study and target given `X`. State that cross-population assumption here; measuring modifiers alone does not establish it.</comment>

<file context>
@@ -0,0 +1,330 @@
+\tau(x)=\E[Y(1)-Y(0)\mid X=x,S=1].
+\]
+
+Average them over the target population:
+\[
+\E_{X\mid S=0}[\tau(X)].
</file context>

Suggested change

	Average them over the target population:
	Assuming \(\E[Y(1)-Y(0)\mid X=x,S=1]=\E[Y(1)-Y(0)\mid X=x,S=0]\), average them over the target population:

[cubic-dev-ai]

P3: The Dahabreh et al. reference gives the wrong year and volume: the article appeared in Biometrics 75(2), June 2019, pages 685–694 (doi:10.1111/biom.13009), not 2020, 76(2). Update year and volume/issue so readers can locate the correct source.

Prompt for AI agents

Check if this issue is valid — if so, understand the root cause and fix it. When an issue isn't valid or won't be fixed in this PR, reply in its thread with the reason and then resolve the thread. At 04-causal-inference/transportability-external-validity/presentation/transportability_external_validity_beamer.tex, line 323:

<comment>The Dahabreh et al. reference gives the wrong year and volume: the article appeared in Biometrics 75(2), June 2019, pages 685–694 (doi:10.1111/biom.13009), not 2020, 76(2). Update year and volume/issue so readers can locate the correct source.</comment>

<file context>
@@ -0,0 +1,330 @@
+\item Pearl, J., and Bareinboim, E. (2011). Transportability of Causal and Statistical Relations. \textit{AAAI}.
+\item Bareinboim, E., and Pearl, J. (2016). Causal Inference and the Data-Fusion Problem. \textit{PNAS}, 113(27), 7345--7352.
+\item Stuart, E. A. et al. (2011). Use of Propensity Scores to Assess the Generalizability of Results from Randomized Trials. \textit{JRSS A}, 174(2), 369--386.
+\item Dahabreh, I. J. et al. (2020). Generalizing Causal Inferences from Individuals in Randomized Trials to All Trial-Eligible Individuals. \textit{Biometrics}, 76(2), 685--694.
+\item Tipton, E. (2013). Improving Generalizations from Experiments Using Propensity Score Subclassification. \textit{JRSS A}, 176(2), 495--519.
+\end{itemize}
</file context>

Suggested change

	\item Dahabreh, I. J. et al. (2020). Generalizing Causal Inferences from Individuals in Randomized Trials to All Trial-Eligible Individuals. \textit{Biometrics}, 76(2), 685--694.
	\item Dahabreh, I. J. et al. (2019). Generalizing Causal Inferences from Individuals in Randomized Trials to All Trial-Eligible Individuals. \textit{Biometrics}, 75(2), 685--694.