{"id":"W4290725887","doi":"10.32614/rj-2022-022","title":"Power and Sample Size for Longitudinal Models in R -- The longpower Package and Shiny App","year":2022,"lang":"en","type":"article","venue":"The R Journal","topic":"Mental Health Research Topics","field":"Psychology","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Weston Brain Institute; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; University of Southern California; Eli Lilly and Company; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Sample size determination; Computer science; Neuroimaging; Statistical power; Alzheimer's Disease Neuroimaging Initiative; Sample (material); R package; Clinical study design; Longitudinal study; Longitudinal data; Clinical trial; Data science; Medical physics; Data mining; Alzheimer's disease; Statistics; Psychology; Medicine; Disease; Mathematics; Psychiatry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003672341,0.00008361915,0.0001148426,0.00004801511,0.0006807794,0.00005862506,0.0003129486,0.00002765837,0.001805086],"category_scores_gemma":[0.0001478287,0.00004842313,0.00003019315,0.0001025601,0.00009757902,0.00007546405,0.0001441699,0.0007599234,0.000003555377],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005861028,"about_ca_system_score_gemma":0.00003728993,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001206959,"about_ca_topic_score_gemma":0.00005415041,"domain_scores_codex":[0.9983178,0.0006650561,0.000203198,0.0001303863,0.0003010315,0.000382487],"domain_scores_gemma":[0.9974597,0.002134986,0.00007031389,0.000222693,0.00002020239,0.00009218429],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.01126043,0.002418723,0.1553965,0.0003200408,0.0004745132,0.0009190466,0.3332135,0.0005076018,0.0003229361,0.1516716,0.2529804,0.09051467],"study_design_scores_gemma":[0.007339076,0.003027289,0.4563152,0.00004065891,0.00005981093,0.006184212,0.05033868,0.001594167,0.00001289896,0.4154719,0.05916304,0.0004530187],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9820306,0.002126709,0.001793164,0.009937095,0.0003558393,0.000640487,0.00006322355,0.000007267195,0.003045566],"genre_scores_gemma":[0.9976188,0.0001038231,0.0002877798,0.001133727,0.0001130267,0.00005913328,9.554038e-7,0.00001296957,0.000669813],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3009187,"threshold_uncertainty_score":0.9991074,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09980713533691159,"score_gpt":0.410800616338218,"score_spread":0.3109934810013064,"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."}}