{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.05222793,0.002899064,0.002947457,0.00397735,0.0008627184,0.003183626,0.00373007,0.002530056,0.1598547],"category_scores_gemma":[0.2792713,0.003469101,0.00451491,0.003313594,0.001759861,0.004707501,0.00385738,0.00552307,0.04939944],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001236732,"about_ca_system_score_gemma":0.003312418,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002038562,"about_ca_topic_score_gemma":0.002414707,"domain_scores_codex":[0.9744499,0.01762405,0.001966276,0.001875946,0.003447827,0.0006359127],"domain_scores_gemma":[0.6665967,0.3033218,0.007556793,0.01325976,0.008316047,0.0009489565],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002066001,0.0002553985,0.007422913,0.006220192,0.001515722,0.0003834648,0.00125092,0.009873144,0.001397271,0.03942841,0.6786267,0.2515598],"study_design_scores_gemma":[0.0053453,0.001425505,0.01989605,0.004372407,0.001463432,0.001184521,0.0004170277,0.1223124,0.01199916,0.2025513,0.6283832,0.0006497305],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.004153092,0.0009418125,0.8094687,0.002375903,0.001253535,0.004679317,0.04469645,0.1190924,0.01333876],"genre_scores_gemma":[0.03275368,0.0006176481,0.8477625,0.001889298,0.0005589439,0.04304588,0.01033595,0.0542962,0.008739903],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.1598547,"threshold_uncertainty_score":0.5347674,"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."}}