{"doi":"10.1002/alz.12214","title":"Development and validation of the Uniform Data Set (v3.0) executive function composite score (UDS3‐EF)","abstract":"INTRODUCTION: Cognitive composite scores offer a means of precisely measuring executive functioning (EF). METHODS: We developed the Uniform Data Set v3.0 EF composite score (UDS3-EF) in 3507 controls from the National Alzheimer's Coordinating Center dataset using item-response theory and applied nonlinear and linear demographic adjustments. The UDS3-EF was validated with other neuropsychological tests and brain magnetic resonance imaging from independent research cohorts using linear models. RESULTS: Final model fit was good-to-excellent: comparative fit index = 0.99; root mean squared error of approximation = 0.057. UDS3-EF scores differed across validation cohorts (controls > mild cognitive impairment > Alzheimer's disease-dementia ≈ behavioral variant frontotemporal dementia; P < 0.001). The UDS3-EF correlated most strongly with other EF tests (βs = 0.50 to 0.85, Ps < 0.001) and more with frontal, parietal, and temporal lobe gray matter volumes (βs = 0.18 to 0.33, Ps ≤ 0.004) than occipital gray matter (β = 0.12, P = 0.04). The total sample needed to detect a 40% reduction in UDS3-EF change (n = 286) was ≈40% of the next best measure (F-words; n = 714). CONCLUSIONS: The UDS3-EF is well suited to quantify EF in research and clinical trials and offers psychometric and practical advantages over its component tests.","journal":"Alzheimer s & Dementia","year":2020,"id":62351,"datarank":1.0705279514609467,"base_score":3.970291913552122,"endowment":3.970291913552122,"self_citation_contribution":0.5955437870328184,"citation_network_contribution":0.4749841644281283,"self_endowment_contribution":0.5955437870328184,"citer_contribution":0.4749841644281283,"corpus_percentile":81.06289162218613,"corpus_rank":2449,"citation_count":52,"citer_count":26,"citers_with_citation_signal":19,"citers_with_endowment":19,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.9036,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":329464,"name":"Breton M. Asken","orcid":"0000-0001-8419-142X","position":1,"is_corresponding":false},{"id":329465,"name":"Kaitlin B. Casaletto","orcid":"0000-0001-5000-7604","position":2,"is_corresponding":false},{"id":329466,"name":"Corrina Fonseca","orcid":"0000-0002-4156-1037","position":3,"is_corresponding":false},{"id":316056,"name":"Michelle You","orcid":null,"position":4,"is_corresponding":false},{"id":230946,"name":"Howard J. Rosen","orcid":"0000-0001-9281-7402","position":5,"is_corresponding":false},{"id":253908,"name":"Adam L. Boxer","orcid":"0000-0002-1215-5064","position":6,"is_corresponding":false},{"id":314700,"name":"Fanny M. Elahi","orcid":"0000-0003-4663-4992","position":7,"is_corresponding":false},{"id":253907,"name":"John Kornak","orcid":"0000-0002-0089-0619","position":8,"is_corresponding":false},{"id":325848,"name":"Dan Mungas","orcid":"0000-0003-2035-7085","position":9,"is_corresponding":false},{"id":253924,"name":"Joel H. Kramer","orcid":"0000-0002-2917-8297","position":10,"is_corresponding":false},{"id":260464,"name":"Adam M. Staffaroni","orcid":"0000-0002-3903-9805","position":0,"is_corresponding":true}],"reference_count":47,"raw_metadata":null,"created_at":"2026-07-18T21:10:11.612909Z","pmid":"33215852","pmcid":"PMC8044003","fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}