{"id":"W2135531855","doi":"10.1108/14757701211228200","title":"More power to you: properties of a more powerful event study methodology","year":2012,"lang":"en","type":"article","venue":"Review of Accounting and Finance","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Null hypothesis; Null (SQL); Estimator; Econometrics; Event study; Event (particle physics); Statistical hypothesis testing; Sample (material); Alternative hypothesis; Sample size determination; Originality; Statistical power; Computer science; Power (physics); Statistics; Data mining; Economics; Mathematics; Psychology; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.218685,0.001364079,0.002263925,0.002722515,0.001573848,0.005124434,0.003415738,0.003455589,0.02102818],"category_scores_gemma":[0.5561322,0.001034354,0.003062941,0.003345588,0.00841435,0.01346532,0.006683854,0.007534023,0.001910322],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001149526,"about_ca_system_score_gemma":0.00272172,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008373277,"about_ca_topic_score_gemma":0.0004944988,"domain_scores_codex":[0.8031969,0.1686201,0.004904761,0.01084438,0.01147446,0.0009593595],"domain_scores_gemma":[0.1838805,0.7488845,0.0115782,0.04649727,0.007644833,0.001514715],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001405808,0.0003899086,0.02792877,0.001498177,0.001180598,0.0006174453,0.004964917,0.01682716,0.001260099,0.6624289,0.007099589,0.2743987],"study_design_scores_gemma":[0.0009320023,0.002285742,0.01090946,0.0006752359,0.0004770412,0.0009229592,0.001172216,0.1010957,0.001676551,0.8506106,0.0290674,0.000175011],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02024185,0.0007463254,0.9633907,0.004433416,0.0005317515,0.0008169755,0.0003290297,0.0003760907,0.009133933],"genre_scores_gemma":[0.4660921,0.0005701915,0.5210164,0.004049113,0.001343765,0.003355948,0.0002951737,0.0003769318,0.00290033],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.218685,"threshold_uncertainty_score":0.9635005,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07254051274649206,"score_gpt":0.2964975405516411,"score_spread":0.223957027805149,"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."}}