{"id":"W1990732953","doi":"10.1002/sim.2435","title":"Pseudo-likelihood methods for longitudinal binary data with non-ignorable missing responses and covariates","year":2005,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Michael's Hospital","funders":"National Cancer Institute; National Heart, Lung, and Blood Institute; National Institute of General Medical Sciences; U.S. Public Health Service","keywords":"Covariate; Missing data; Categorical variable; Statistics; Parametric statistics; Estimating equations; Econometrics; Expectation–maximization algorithm; Outcome (game theory); Mathematics; Computer science; Maximum likelihood","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":[0.04626171,0.002157088,0.003399933,0.003692439,0.001124974,0.003271954,0.007829505,0.003449407,0.00691089],"category_scores_gemma":[0.154411,0.00249916,0.003433299,0.004806914,0.003865923,0.005905563,0.005430612,0.006201401,0.002726726],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001577207,"about_ca_system_score_gemma":0.003973496,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003205188,"about_ca_topic_score_gemma":0.003356644,"domain_scores_codex":[0.9615839,0.03313635,0.001087261,0.001710362,0.002172056,0.0003101681],"domain_scores_gemma":[0.8279058,0.1525535,0.006452598,0.00820517,0.004102975,0.0007799756],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006901635,0.0002492724,0.006473437,0.002240845,0.001112344,0.0009441327,0.00138132,0.2539168,0.001112067,0.4843242,0.0080442,0.2395113],"study_design_scores_gemma":[0.0001476737,0.0001076482,0.0007085396,0.0002435368,0.00007086324,0.0003007567,0.0001088219,0.5891445,0.0005021893,0.4001503,0.008423256,0.00009194115],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0006501646,0.000338255,0.9982374,0.0001738834,0.00004095843,0.00008751357,0.0001023835,0.0001930232,0.0001765264],"genre_scores_gemma":[0.04271134,0.001096681,0.9498934,0.000473108,0.0002949174,0.002026349,0.001129534,0.0004603736,0.001914352],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04626171,"threshold_uncertainty_score":0.2446582,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.122764640882849,"score_gpt":0.4810958116797321,"score_spread":0.3583311707968831,"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."}}