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The 132 pages that link to Causal inference, each with the reason it gives.

• CounterfactualCompared with: Counterfactuals are claims or quantities; causal inference is the broader process of evaluating causal effects.

• System boundaryRelated: A causal analysis must decide which variables and pathways belong in its model.

• Climate change attributionNarrower topic: Climate attribution adapts causal reasoning to a system with interacting drivers and limited experiments.

• Comparative staticsCompared with: Comparative statics predicts model-based effects; causal inference seeks effects identified from evidence.

• Counterfactual historyRelated: Historical alternatives test which conditions plausibly made a difference to an outcome.

• Quasi-experimentNarrower topic: Quasi-experiments are one family of designs for estimating causal effects.

• AbductionRelated: Many abductive explanations propose an unobserved cause for observed effects.

• Circumstantial evidenceRelated: A causal claim may be inferred from circumstances, but association alone does not establish it.

• ExperimentRelated: Experiments are designed to support causal conclusions by controlling alternative explanations.

• OptogeneticsRelated: Selective stimulation helps distinguish causal circuit effects from mere correlations.

• Program evaluationNarrower topic: It explains the assumptions behind claims that a program produced observed effects.

• Agglomeration economiesRelated: Productive firms may choose dense locations, complicating estimates of the effect of proximity itself.

• Empirical evidenceRelated: Observed associations alone do not establish that one event caused another.

• Instrumental variableNarrower topic: Instrumental variables are one strategy for identifying effects when direct adjustment is inadequate.

• AdditionalityNarrower topic: It supplies methods for distinguishing intervention effects from background changes.

• Historical sociologyRelated: Historical comparisons must distinguish causal mechanisms from coincidence and retrospective storytelling.

• Large igneous provinceRelated: Temporal coincidence alone cannot establish that a province caused an extinction or climate shift.

• Pattern recognitionCompared with: Detecting a recurring association does not by itself establish its cause.

• Policy analysisRelated: Claims about likely policy effects depend on credible causal reasoning.

• Quantitative researchRelated: Numerical association alone does not establish that one variable caused another.

• Scientific explanationRelated: Causal claims often distinguish explanations from descriptions of mere association.

• Alternate historyRelated: Plausible timelines depend on tracing how a divergence could produce later changes.

• Comparative politicsRelated: Comparative claims about institutional effects depend on separating causes from correlation.

• Intolerance of uncertaintyRelated: Associations with anxiety do not by themselves establish that intolerance of uncertainty causes it.

• Model selectionCompared with: A model’s predictive adequacy alone does not establish that its causal claims are valid.

• Protective factorRelated: An observed association does not establish that a proposed protective factor caused lower harm.

• Basketball analyticsCompared with: Observed player statistics alone do not establish that a player caused a team’s results.

• Scatter plotCompared with: Visible association alone does not establish that one plotted variable causes the other.

• Control groupNarrower topic: A control group supports causal estimates by approximating what would happen without the intervention.

• Experimental methodNarrower topic: Experiments are designed to support causal conclusions, not merely describe associations.

• Explainable artificial intelligenceRelated: A feature’s influence on a prediction does not by itself establish a causal relationship.

• Reparations for slaveryRelated: Estimating slavery’s contribution to present disparities requires separating overlapping historical causes.

• Social scienceRelated: Social scientists use it to separate causal effects from mere association.

• BiostatisticsRelated: Biomedical decisions often require causal effects, not merely observed associations.

• Ceteris paribusRelated: Causal claims require separating an effect from changes in other relevant conditions.

• Data miningCompared with: A mined association alone does not establish that one event causes another.

• Econometric modelRelated: Econometric models can estimate causal effects when their identifying assumptions hold.

• Econometric SocietyRelated: It captures a central modern challenge for empirical economics and econometric research.

• MulticollinearityRelated: Whether to retain correlated causes depends on the causal question, not just coefficient precision.

• Data scienceRelated: It addresses questions that prediction alone cannot answer.

• Experimental economicsNarrower topic: Experimental economics uses controlled variation to strengthen causal conclusions.

• Molecular epidemiologyRelated: Molecular associations alone do not establish that a biological factor caused disease.

• Suicide contagionNarrower topic: Exposure and suicidal behavior may coincide without exposure causing the change.

• Data analysisRelated: It separates causal questions from descriptive patterns and associations.

• ExtrapolationCompared with: Causal estimates rely on assumptions about interventions, not merely extending an observed association.

• Mathematical statisticsRelated: Its estimands and identification assumptions extend statistical inference beyond association.

• News analysisRelated: Claims about why an event happened require more than noting that factors occurred together.

• Nonparametric statisticsRelated: Flexible nuisance estimates can help causal analyses, but do not replace identification assumptions.

• CliometricsRelated: Historical studies use causal designs to distinguish effects from coincidence.

• Race and intelligenceRelated: Group comparisons require causal reasoning to distinguish ancestry from social exposures and confounders.