{"id":"W1576666808","doi":"10.1111/psyp.12299","title":"Modeling nonlinear relationships in <scp>ERP</scp> data using mixed‐effects regression with <scp>R</scp> examples","year":2014,"lang":"en","type":"article","venue":"Psychophysiology","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":110,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Psychology; Mixed model; Regression analysis; Nonlinear system; Linearity; Linear regression; Econometrics; Structural equation modeling; Social psychology; Statistics; Mathematics","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":[0.00805988,0.001197573,0.0008897192,0.001361291,0.0004629534,0.001400439,0.001789536,0.001374329,0.003772052],"category_scores_gemma":[0.01554626,0.0007255248,0.003170788,0.001562744,0.0007843426,0.001499095,0.001087163,0.001936099,0.001016962],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004981366,"about_ca_system_score_gemma":0.000889584,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005195297,"about_ca_topic_score_gemma":0.007010315,"domain_scores_codex":[0.997789,0.001435474,0.00009770715,0.0003481685,0.0002250895,0.0001045764],"domain_scores_gemma":[0.9935615,0.005166421,0.0003841625,0.0004631282,0.0003593706,0.0000654553],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005608844,0.0003952416,0.0160262,0.0007058816,0.001296343,0.0009783518,0.0009485921,0.6034581,0.01311265,0.1072852,0.003921357,0.2513111],"study_design_scores_gemma":[0.00002050597,0.000115272,0.001848392,0.00003149469,0.00009176345,0.0001258481,0.00004169274,0.9646766,0.001646636,0.02910022,0.002258478,0.00004296972],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01394662,0.0001812668,0.9844723,0.0001845565,0.00003854428,0.0000400325,0.000118813,0.0005940219,0.0004238265],"genre_scores_gemma":[0.3338919,0.0006197234,0.6596246,0.0002016121,0.00008483069,0.0005743556,0.0006010777,0.0004234001,0.003978468],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00805988,"threshold_uncertainty_score":0.04262519,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0917921303502375,"score_gpt":0.3028296807109004,"score_spread":0.2110375503606629,"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."}}