{"id":"W2033411871","doi":"10.1198/0003130031450","title":"Type I Error Inflation in the Presence of a Ceiling Effect","year":2003,"lang":"en","type":"article","venue":"The American Statistician","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":125,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Clinical Evaluative Sciences","funders":"","keywords":"Statistics; Ceiling (cloud); Econometrics; Statistical significance; Variables; Ceiling effect; Type I and type II errors; Mathematics; Standard error; Alcohol consumption; Variable (mathematics); Linear regression; Psychology; Medicine; Engineering; Biology; Alcohol","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":["metaresearch"],"category_scores_codex":[0.2854362,0.00143345,0.003374082,0.003136098,0.002106835,0.004373481,0.003061216,0.005061866,0.006183084],"category_scores_gemma":[0.6522195,0.001328904,0.003214225,0.004170565,0.006778882,0.005098138,0.004317241,0.007547798,0.001398785],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00376123,"about_ca_system_score_gemma":0.004257806,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002540388,"about_ca_topic_score_gemma":0.002456731,"domain_scores_codex":[0.6059636,0.2925323,0.0238489,0.03373709,0.03969298,0.004225146],"domain_scores_gemma":[0.1538204,0.7199995,0.04144152,0.06562034,0.0176688,0.001449445],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004793254,0.000705431,0.1994938,0.002970749,0.00448009,0.004020738,0.008454369,0.03375942,0.002543346,0.3204053,0.04613732,0.3722361],"study_design_scores_gemma":[0.00133208,0.001812511,0.09776285,0.003235465,0.003152108,0.005151125,0.003052075,0.1954896,0.01010729,0.6492752,0.02898126,0.0006484783],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05141947,0.003611854,0.9071278,0.009989097,0.003639398,0.002366991,0.001142239,0.001430195,0.01927299],"genre_scores_gemma":[0.6686611,0.001134073,0.3098027,0.008419215,0.00156442,0.004452265,0.0007937006,0.0004359784,0.004736553],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7145638,"threshold_uncertainty_score":0.8811843,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09602044591037069,"score_gpt":0.4371410127819303,"score_spread":0.3411205668715597,"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."}}