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If you are uploading a letter concerning an article: Copyright © 2015 by AAN Enterprises, Inc.LaPelle has received personal compensation for activities with the University of Massachusetts Medical School as a consultant. Tilley has received personal compensation for activities with the University of Texas School of Public Health. Wang has received personal compensation for activities with the University of Texas. Luo has received personal compensation for activities with the University of Texas. Goetz has received personal compensation in an editorial capacity for Oxford University Press, Elsevier Publish Dr. Goetz has received personal compensation for activities with Boston Scientific, CHDI, Centurion, ClearView, Frankel Group, and Ingenix. The Rush Center is supported by the Parkinson's Disease Foundation.ĭisclosure: Dr. Study Supported by: A grant from the Movement Disorder Society. The validation sample confirmed these cutoff values.ĬONCLUSIONS: These analyses are useful for clinical and research use to calculate valid surrogate MDS-UPDRS Part scores when missing items fall within the identified threshold and give scientific justification for rejecting partially completed ratings falling below threshold. To provide valid Part scores applicable across all HY stages when random item entries are missing, one missing item from Part I, two from Part II, seven from Part III, but none from Part IV can be allowed. RESULTS: To provide valid Part scores applicable across all HY stages when the same items are consistently missing, one missing item from Part I, one from Part II, three from Part III, but none from Part IV can be allowed. A second confirmatory sample was selected from the MDS-UPDRS international translation program. We examined three Hoehn and Yahr (HY) categories (Stages 1-2, 3, and 4-5) each with 160 randomly selected entries. The maximal number of missing values retaining CCC > 0.95 determined the threshold for rendering a valid prorated score. Linn’s Concordance Correlation Coefficient (CCC) compared scores without missing values with prorated scores from sequentially increasing missing values. We developed a rigorous, scale-specific, data-based approach to handling missing values and generating valid prorated scores when the MDS-UPDRS is incomplete.ĭESIGN/METHODS: From two large MDS-UPDRS datasets, we deleted item scores, either consistently (same items across all subjects) or randomly (different items across subjects). OBJECTIVE: To define the number of missing values permissible to render valid total scores for each Part of the MDS-UPDRS.īACKGROUND: Rating scale missing values are problematic and imputation strategies have been developed as general guidelines to reject an incomplete rating or create a surrogate score.