{"id":"W4285042994","doi":"10.22215/etd/2022-15135","title":"Approximate Methods For Analyzing Semi-Parametric Longitudinal Models With Non-Ignorable Missing Responses","year":2022,"lang":"en","type":"dissertation","venue":"","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Qassim University","keywords":"Estimator; Parametric statistics; Missing data; Spline (mechanical); Semiparametric model; Mathematics; Linear model; Mixed model; Conditional expectation; Generalized linear mixed model; Parametric model; Applied mathematics; Variance function; Generalized linear model; Statistics; Computer science","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":[0.02429682,0.001644745,0.002385159,0.002271201,0.000708935,0.001821583,0.004498858,0.00205388,0.005274104],"category_scores_gemma":[0.1016386,0.001521907,0.00280946,0.00270504,0.002798347,0.00378608,0.00372715,0.004346008,0.001036713],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001514874,"about_ca_system_score_gemma":0.002194376,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00205496,"about_ca_topic_score_gemma":0.002141712,"domain_scores_codex":[0.9856031,0.01167399,0.0003751033,0.0008488075,0.001258171,0.0002408845],"domain_scores_gemma":[0.9030402,0.08640252,0.003296051,0.004920201,0.001942913,0.0003981482],"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":[0.0001362751,0.0001039381,0.002495073,0.0007098273,0.0005530783,0.0001763061,0.0005432549,0.3057617,0.0008526893,0.6028064,0.001749658,0.08411191],"study_design_scores_gemma":[0.00002675058,0.00007328958,0.0003761634,0.0001080389,0.00005780414,0.00007604003,0.00006166966,0.6042683,0.0003579856,0.392137,0.002428821,0.00002815701],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001042527,0.0003006341,0.9981913,0.0001073452,0.00001294002,0.00002697871,0.00004512766,0.00005994029,0.0002132602],"genre_scores_gemma":[0.1107123,0.002140377,0.8808001,0.0003921461,0.0002617119,0.001653769,0.0007466609,0.0002377538,0.003055274],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02429682,"threshold_uncertainty_score":0.1284954,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1675747254810343,"score_gpt":0.4758706114412193,"score_spread":0.308295885960185,"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."}}