{"id":"W1969750978","doi":"10.1002/cjs.11155","title":"Weighting in the regression analysis of survey data with a cross‐national application","year":2012,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Economic and Social Research Council","keywords":"Weighting; Statistics; Econometrics; Logistic regression; Regression analysis; Mathematics; Survey data collection; European Social Survey; Regression; Variance (accounting); Survey sampling; Politics; Economics; Sociology; Demography; Political science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.1518789,0.001618037,0.002971105,0.004663249,0.001407191,0.00302129,0.004102977,0.003433647,0.004307851],"category_scores_gemma":[0.3886461,0.001607047,0.003180357,0.007313027,0.004734549,0.003879472,0.00468005,0.004079511,0.0009016963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001899677,"about_ca_system_score_gemma":0.00141096,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003339556,"about_ca_topic_score_gemma":0.002365092,"domain_scores_codex":[0.8070068,0.170314,0.005279231,0.009017847,0.007497263,0.0008848939],"domain_scores_gemma":[0.6294908,0.3006355,0.01439539,0.04501922,0.009789391,0.0006697089],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000380148,0.0002885941,0.02524984,0.001164429,0.002178679,0.0004996615,0.001301046,0.1185967,0.002185095,0.5471382,0.00422168,0.2967959],"study_design_scores_gemma":[0.0001475369,0.0004273423,0.006695713,0.0004039268,0.000378439,0.000340765,0.0002588833,0.5742823,0.002455233,0.40219,0.01229702,0.0001228328],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005533765,0.0003867687,0.993072,0.0001898629,0.00008075788,0.0001712781,0.00004421227,0.00008972237,0.0004317047],"genre_scores_gemma":[0.1995255,0.001018971,0.7937716,0.0004371113,0.0003706529,0.002317389,0.000355903,0.0001505739,0.002052309],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1518789,"threshold_uncertainty_score":0.8032219,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1785375592838139,"score_gpt":0.417553547512225,"score_spread":0.239015988228411,"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."}}