{"id":"W2043769717","doi":"10.2501/s0021849907070298","title":"Perils of Using OLS to Estimate Multimedia Communications Effects","year":2007,"lang":"en","type":"article","venue":"Journal of Advertising Research","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Quest University Canada","funders":"","keywords":"Ordinary least squares; Profitability index; Estimation; Marketing; Advertising; Econometrics; Marketing mix modeling; Shareholder; Economics; Marketing mix; Business; Marketing effectiveness; Return on marketing investment; Corporate governance","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":[0.01802681,0.0007953675,0.0006086984,0.001193937,0.0005302975,0.00235037,0.0009224702,0.0008879801,0.003934721],"category_scores_gemma":[0.08891945,0.0004610117,0.0008852025,0.001489395,0.0008955316,0.001652188,0.0009166674,0.0009659615,0.0007077445],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008296678,"about_ca_system_score_gemma":0.001088564,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02104992,"about_ca_topic_score_gemma":0.01132955,"domain_scores_codex":[0.9892943,0.008313153,0.0003472486,0.0006181765,0.001113971,0.0003132197],"domain_scores_gemma":[0.8907825,0.09569416,0.006519518,0.004326514,0.002444688,0.0002325209],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001067899,0.0006234747,0.5620239,0.0003758003,0.003203173,0.0003874788,0.00100782,0.2077458,0.002109286,0.04677626,0.006095392,0.1685837],"study_design_scores_gemma":[0.000185645,0.0007025652,0.165724,0.0001636837,0.0008815858,0.0001283388,0.001961276,0.7893767,0.006272511,0.0292605,0.005227975,0.0001151995],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.7960093,0.0007227632,0.1821814,0.002621971,0.0001511619,0.0003273039,0.001006075,0.0005259581,0.01645402],"genre_scores_gemma":[0.9823439,0.0001364682,0.01572167,0.0002413807,0.00004125388,0.00008938415,0.0002939446,0.00003418991,0.001097872],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9819732,"threshold_uncertainty_score":0.09533602,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09446965299015343,"score_gpt":0.4426009793145355,"score_spread":0.348131326324382,"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."}}