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The biomarker data is incomplete (missing and irregular) multivariate longitudinal data. We propose a normal model with structured covariance designed for our setting. To sample from the posterior distribution of parameters, we develop a Markov Chain Monte Carlo (MCMC) algorithm to address the positive definiteness constraint on the structured correlation matrix. In particular, we propose a novel approach to compute the support of the parameters in the structured correlation matrix; we modify the approach from [1] on the set of the largest possible submatrices of the correlation matrix, where the correlation parameter is a unique element. For each posterior sample, we compute the optimal weights of our construct. We conduct data analysis and simulation studies to evaluate the algorithm and the frequentist properties of the posteriors of correlations and weights. We found that the lower extremities are the most responsive muscles at the early and late ambulatory disease stages, and the biceps brachii is the most responsive at the nonambulatory disease stage.<\/jats:p>","DOI":"10.1002\/sim.70252","type":"journal-article","created":{"date-parts":[[2025,9,9]],"date-time":"2025-09-09T02:33:30Z","timestamp":1757385210000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A New Algorithm for Sampling Parameters in a Structured Correlation Matrix With Application to Estimating Optimal Combinations of Muscles to Quantify Progression in Duchenne Muscular Dystrophy"],"prefix":"10.1002","volume":"44","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-0972-2338","authenticated-orcid":false,"given":"Michael K.","family":"Kim","sequence":"first","affiliation":[{"name":"Department of Statistics University of Florida  Gainesville Florida USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9856-9486","authenticated-orcid":false,"given":"Michael J.","family":"Daniels","sequence":"additional","affiliation":[{"name":"Department of Statistics University of Florida  Gainesville Florida USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"William D.","family":"Rooney","sequence":"additional","affiliation":[{"name":"Advanced Imaging Research Center Oregon Health and Science University  Portland Oregon USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rebecca J.","family":"Willcocks","sequence":"additional","affiliation":[{"name":"Department of Physical Therapy University of Florida  Gainesville Florida USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Glenn A.","family":"Walter","sequence":"additional","affiliation":[{"name":"Department of Physiology and Aging University of Florida  Gainesville Florida USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Krista H.","family":"Vandenborne","sequence":"additional","affiliation":[{"name":"Department of Physical Therapy University of Florida  Gainesville Florida USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2025,9,8]]},"reference":[{"key":"e_1_2_11_2_1","first-page":"1281","article-title":"Modeling Covariance Matrices in Terms of Standard Deviations and Correlations, With Application to Shrinkage","volume":"10","author":"Barnard J.","year":"2000","journal-title":"Statistica Sinica"},{"issue":"404","key":"e_1_2_11_3_1","first-page":"1014","article-title":"Newton\u00e2euro Raphson and EM Algorithms for Linear Mixed\u2010Effects Models for Repeated\u2010Measures Data","volume":"83","author":"Lindstrom M. 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