{"id":"W4390051166","doi":"10.1177/1536867x231212432","title":"csa2sls: A complete subset approach for many instruments using Stata","year":2023,"lang":"en","type":"article","venue":"The Stata Journal Promoting communications on statistics and Stata","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Estimator; Mean squared error; Statistics; Monte Carlo method; Econometrics; Instrumental variable; Least-squares function approximation; Mathematics; Bias of an estimator; Computer science; Minimum-variance unbiased estimator","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":[],"consensus_categories":[],"category_scores_codex":[0.01720587,0.002113198,0.002110393,0.005504871,0.001239415,0.002625824,0.002822154,0.001147034,0.09952926],"category_scores_gemma":[0.1038893,0.001996341,0.002735124,0.007333441,0.0007245112,0.002757308,0.003923349,0.00352668,0.01863744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000567004,"about_ca_system_score_gemma":0.004729415,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005430187,"about_ca_topic_score_gemma":0.008186187,"domain_scores_codex":[0.9817622,0.01319193,0.001716092,0.001387532,0.001426436,0.0005158479],"domain_scores_gemma":[0.8904816,0.0897633,0.004826661,0.009406974,0.004789707,0.0007318215],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009108675,0.0004007949,0.02917493,0.002574889,0.002805833,0.0009409909,0.002797123,0.0342484,0.001842625,0.05421217,0.3932002,0.4768911],"study_design_scores_gemma":[0.001117149,0.0006207597,0.01434944,0.0009170105,0.0008768445,0.0005556052,0.001537747,0.3918268,0.006763672,0.1370668,0.443997,0.0003711363],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.005859394,0.0001712368,0.9323652,0.000612342,0.0002020399,0.001058833,0.02348226,0.03282692,0.003421762],"genre_scores_gemma":[0.04304687,0.0001655174,0.9223675,0.0003758526,0.0001580078,0.00487196,0.01473368,0.01098384,0.003296635],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.09952926,"threshold_uncertainty_score":0.3329586,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1563916626367033,"score_gpt":0.3397580369528209,"score_spread":0.1833663743161176,"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."}}