{"id":"W2587996994","doi":"10.1093/aje/163.suppl_11.s154-a","title":"Estimation of Parameters in Logistic Regression Models with Multiplicative Measurement Error","year":2006,"lang":"en","type":"article","venue":"American Journal of Epidemiology","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Logistic regression; Statistics; Estimation; Multiplicative function; Regression analysis; Regression; Regression dilution; Mathematics; Cross-sectional regression; Econometrics; Nonlinear regression; Polynomial regression; Engineering","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":[0.05446286,0.002785188,0.004767922,0.003440551,0.001097079,0.004396939,0.0062115,0.00481395,0.001166632],"category_scores_gemma":[0.3869899,0.003557386,0.003357023,0.003922093,0.00378688,0.009485063,0.006797792,0.006564215,0.0005887608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001510833,"about_ca_system_score_gemma":0.002014722,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002893428,"about_ca_topic_score_gemma":0.001396626,"domain_scores_codex":[0.9482068,0.04157256,0.002439729,0.003902321,0.002972497,0.0009061053],"domain_scores_gemma":[0.6784468,0.2926975,0.01154482,0.01236502,0.004042773,0.0009030597],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0006773011,0.0002270618,0.02543962,0.0008245423,0.001051182,0.0007484959,0.001247547,0.5930322,0.001599082,0.2300629,0.002700062,0.14239],"study_design_scores_gemma":[0.00006566886,0.00007388405,0.001572956,0.0001089578,0.0001352298,0.0002014552,0.0001067742,0.8520858,0.0007704316,0.1443163,0.0004849519,0.00007762583],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008001351,0.0003200671,0.9909491,0.0003650429,0.00002670068,0.00004125622,0.0000512752,0.0001288433,0.0001163842],"genre_scores_gemma":[0.4366673,0.002374227,0.5560692,0.0003506145,0.0002824733,0.001289654,0.0008786979,0.0002609326,0.001826961],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05446286,"threshold_uncertainty_score":0.2880306,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3193392347408081,"score_gpt":0.4770914298080688,"score_spread":0.1577521950672607,"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."}}