{"id":"W4396799016","doi":"10.1002/sim.10089","title":"Novel non‐linear models for clinical trial analysis with longitudinal data: A tutorial using <scp>SAS</scp> for both frequentist and Bayesian methods","year":2024,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"College of Veterinarians of British Columbia","funders":"National Institute on Aging; National Institutes of Health","keywords":"Frequentist inference; Categorical variable; Bayesian probability; Repeated measures design; Random effects model; Computer science; Inference; Mixed model; Statistics; Bayesian inference; Linear model; Generalized linear mixed model; Mathematics; Econometrics; Artificial intelligence; Medicine","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.02535194,0.0004961464,0.002679626,0.0004552711,0.0001539259,0.0001230215,0.0005789241,0.000390653,0.0000313812],"category_scores_gemma":[0.2057364,0.0003705869,0.0001942859,0.0008349738,0.0009284158,0.0001854365,0.0002225081,0.000704678,5.278357e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000110864,"about_ca_system_score_gemma":0.000398974,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001444941,"about_ca_topic_score_gemma":0.0002464135,"domain_scores_codex":[0.9931164,0.0008852778,0.003041702,0.001545783,0.0007286543,0.0006822125],"domain_scores_gemma":[0.7904444,0.2074275,0.0005140492,0.0009834865,0.0003081895,0.0003223829],"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":[0.01567122,0.001472251,0.0007481747,0.004667665,0.00912434,0.000294513,0.001146698,0.0005774306,0.0002324483,0.8817662,0.03454423,0.04975482],"study_design_scores_gemma":[0.02143306,0.001276211,0.00004426779,0.0002968838,0.005806467,0.000008004302,0.00008671925,0.5004306,0.000005537885,0.4696245,0.0008468381,0.0001409526],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0005149062,0.0002804743,0.983961,0.0001362178,0.00448552,0.002789878,0.007671187,0.00007320737,0.00008763756],"genre_scores_gemma":[0.001194826,0.0001384093,0.9923129,0.00008524227,0.005524468,0.0001883957,0.0002837432,0.000124212,0.0001477833],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4998532,"threshold_uncertainty_score":0.9998746,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7321217157620442,"score_gpt":0.6629236950961048,"score_spread":0.06919802066593939,"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."}}