{"id":"W4415668209","doi":"10.3758/s13428-025-02783-3","title":"Errors-in-variables regression as a viable approach to mediation analysis with random error-tainted measurements: Estimation, effectiveness, and an easy-to-use implementation","year":2025,"lang":"en","type":"article","venue":"Behavior Research Methods","topic":"Mental Health Research Topics","field":"Psychology","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Regression analysis; Mediation; Observational error; Ordinary least squares; Regression; Regression diagnostic; Errors-in-variables models; Instrumental variable; Standard error; Linear regression","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":[0.1906192,0.003212246,0.003724362,0.003026275,0.001287662,0.003624825,0.00541995,0.002839299,0.01478473],"category_scores_gemma":[0.382371,0.002551737,0.004123348,0.003846892,0.001902345,0.005922577,0.004324415,0.006846413,0.002230992],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008328159,"about_ca_system_score_gemma":0.003685844,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003642204,"about_ca_topic_score_gemma":0.004711936,"domain_scores_codex":[0.7770072,0.2059779,0.004011345,0.005759405,0.006524201,0.0007198985],"domain_scores_gemma":[0.5731547,0.3786663,0.007917024,0.03258855,0.006864226,0.0008092506],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.003958033,0.003234355,0.03543691,0.002605756,0.009086575,0.0003485979,0.003823747,0.01659547,0.002910803,0.1099394,0.01484158,0.7972187],"study_design_scores_gemma":[0.004635824,0.008702651,0.02952029,0.0024607,0.005642276,0.0008673837,0.002009079,0.5323468,0.01507044,0.3538382,0.04412058,0.0007857104],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003863644,0.0002010689,0.9913234,0.0005183216,0.000263274,0.001212377,0.0002484573,0.001384104,0.0009854432],"genre_scores_gemma":[0.0819917,0.0002755302,0.9105583,0.0003339357,0.0001615673,0.004282778,0.0001844949,0.0005613061,0.001650299],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1906192,"threshold_uncertainty_score":0.9981106,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3125196999863581,"score_gpt":0.6438098672918707,"score_spread":0.3312901673055126,"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."}}