{"id":"W4416993465","doi":"10.1186/s12874-025-02721-z","title":"Omitting patients with no follow-up leads to bias when using inverse-intensity weighted GEEs to handle irregular and informative assessment times","year":2025,"lang":"en","type":"article","venue":"BMC Medical Research Methodology","topic":"Medication Adherence and Compliance","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto; University Health Network; Institute for Clinical Evaluative Sciences; Hospital for Sick Children; Public Health Ontario","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"MEDLINE; Task (project management); Reliability (semiconductor); R package","routes":{"ca_aff":true,"ca_fund":true,"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":[0.1538556,0.001965736,0.003696228,0.001169214,0.0008887644,0.00256006,0.003216597,0.002324099,0.002908745],"category_scores_gemma":[0.3110209,0.001133343,0.00567737,0.00161639,0.002460491,0.002777897,0.002604232,0.004267533,0.000520526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001398801,"about_ca_system_score_gemma":0.003370746,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008316691,"about_ca_topic_score_gemma":0.006376984,"domain_scores_codex":[0.9229714,0.06536119,0.003589862,0.004447326,0.002412978,0.001217221],"domain_scores_gemma":[0.6608245,0.2933763,0.01933301,0.01958727,0.005697643,0.001181251],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.008328205,0.0006373794,0.1490717,0.001927002,0.009610847,0.002095313,0.002274999,0.5334234,0.002347034,0.05289565,0.01101048,0.2263779],"study_design_scores_gemma":[0.002073927,0.001298279,0.01964808,0.0006735256,0.002721745,0.0009829345,0.0002874662,0.8437225,0.002473427,0.1165548,0.00931728,0.0002460105],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09406064,0.001692423,0.8965057,0.002549203,0.0003415633,0.001233419,0.001033155,0.0009080837,0.001675902],"genre_scores_gemma":[0.702732,0.0007650167,0.2872466,0.002589272,0.0001837697,0.002770309,0.001555469,0.000381429,0.001776193],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8461444,"threshold_uncertainty_score":0.8136761,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3893173003413801,"score_gpt":0.5139301561461168,"score_spread":0.1246128558047367,"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."}}