{"id":"W4297412566","doi":"10.1002/cjs.11728","title":"Nonparametric tests for treatment effect heterogeneity in observational studies","year":2022,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Observational study; Nonparametric statistics; Propensity score matching; Econometrics; Statistics; Statistic; Parametric statistics; Confounding; Test statistic; Normality; Treatment effect; Asymptotic distribution; Mathematics; Average treatment effect; Statistical hypothesis testing; Computer science; Medicine; Estimator","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.1358738,0.0008135205,0.002671137,0.00669073,0.0008246432,0.002962446,0.004300184,0.003109517,0.004240737],"category_scores_gemma":[0.5371369,0.0005642755,0.00294516,0.005107094,0.006520383,0.003936329,0.003359291,0.003934179,0.0003040606],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001516856,"about_ca_system_score_gemma":0.002225579,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001123879,"about_ca_topic_score_gemma":0.0004514488,"domain_scores_codex":[0.8276747,0.1471372,0.006019681,0.006876505,0.01137773,0.0009141109],"domain_scores_gemma":[0.3030319,0.6502269,0.01752675,0.02307314,0.005427641,0.0007137684],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001536547,0.0003295244,0.06353936,0.003323975,0.009602584,0.001580398,0.001654017,0.08163057,0.001737129,0.5388661,0.007671657,0.2885281],"study_design_scores_gemma":[0.0004519896,0.0006082007,0.01664245,0.0008075344,0.0006311935,0.0006923722,0.0004289441,0.2024861,0.001267629,0.7712249,0.004638949,0.0001196996],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03813141,0.002877787,0.9528462,0.001661596,0.000303326,0.0006236697,0.0007503468,0.0003908747,0.002414881],"genre_scores_gemma":[0.8209531,0.0007371129,0.173436,0.0006835076,0.0004893084,0.002303353,0.0006625064,0.0001158858,0.0006192586],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1358738,"threshold_uncertainty_score":0.718578,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4140206464667522,"score_gpt":0.4684697448995436,"score_spread":0.05444909843279139,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}