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linear mixed-effects models with repeated measures  (SAS institute)


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    SAS institute linear mixed-effects models with repeated measures
    Linear Mixed Effects Models With Repeated Measures, supplied by SAS institute, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/mixed-effects+repeated-measures+models/repeated+measures+anova/pmc12094188-136-11-18
    Average 90 stars, based on 1 article reviews
    linear mixed-effects models with repeated measures - by Bioz Stars, 2026-09
    90/100 stars

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    other:

    Article Title: Internet-based cognitive behavior therapy for major depressive disorder: A randomized controlled trial
    Article Snippet: HLM analyses implemented mixed-effects repeated-measures models using SAS (version 9.2) PROC MIXED (SAS Institute Inc., Cary, NC).



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    mixed-effects models for repeated measures  (SAS institute)
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    Change from baseline in 4‐m gait speed at Month 6 based on multiple imputation in the PP population. Missing data are imputed using multiple imputation. Analysis is based on mixed‐effect model for repeated measurements <t>(MMRM)</t> with treatment, visit, center, gender, and treatment * visit as fixed effects and baseline value as a covariate. LS, least square; SE, standard error.
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    Change from baseline in 4‐m gait speed at Month 6 based on multiple imputation in the PP population. Missing data are imputed using multiple imputation. Analysis is based on mixed‐effect model for repeated measurements (MMRM) with treatment, visit, center, gender, and treatment * visit as fixed effects and baseline value as a covariate. LS, least square; SE, standard error.

    Journal: Journal of Cachexia, Sarcopenia and Muscle

    Article Title: BIO101 in Sarcopenic Seniors at Risk of Mobility Disability: Results of a Double‐Blind Randomised Interventional Phase 2b Trial

    doi: 10.1002/jcsm.13750

    Figure Lengend Snippet: Change from baseline in 4‐m gait speed at Month 6 based on multiple imputation in the PP population. Missing data are imputed using multiple imputation. Analysis is based on mixed‐effect model for repeated measurements (MMRM) with treatment, visit, center, gender, and treatment * visit as fixed effects and baseline value as a covariate. LS, least square; SE, standard error.

    Article Snippet: A mixed‐effects model repeated measurement (MMRM) model with fixed factors of treatment, centres, baseline score and sex was used (in SAS v9.3) to estimate the CFB of the 400MWT GS at Month 6/9 between each active arm and the placebo group (after adjustment for multiplicity due to the two doses of active treatment by the Hochberg procedure).

    Techniques: