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lme function in  (MathWorks Inc)


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    MathWorks Inc lme function in
    Lme Function In, supplied by MathWorks Inc, 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/lme+function/med_rxiv__2025__07__11__25331379-215-100-103
    Average 90 stars, based on 1 article reviews
    lme function in - by Bioz Stars, 2026-11
    90/100 stars

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    Article Title: Knowing where to go: Spatial memory guides eye and body movements in a naturalistic visual search task
    Article Snippet: Model estimates were obtained with the lme function in Matlab (version R2022b), using the Restricted Maximum Likelihood estimation method and Cholesky parameterization to determine the variance-covariance structure (default method in Matlab).

    Article Title: Polymorphism of the beta(2)-adrenergic receptor gene and desensitization in human airway smooth muscle.
    Article Snippet: The variance components for random effects were estimated by using restricted maximum likelihood via the function lme in the S-PLUS (MathWorks, Seattle, WA, 1996) software package.

    Article Title: More than the sum of their parts: A Behavioral Tractography analysis of distress wellbeing and context reveals dynamic signatures of psychosis and autism
    Article Snippet: We estimated association strength between cross-sectional variables from the same EMA assessment as the slope coefficient of a Linear Mixed Regression (LMR) with a random intercept for each subject; formalized as follows: Y ij = β 0 + β 1 X ij + u j + ε ij where Y ij is the outcome variable for subject j at observation i, X ij is the predictor variable for subject j at observation i, β 0 is the fixed intercept, β 1 is the fixed slope, u j is the random intercept per subject, ε ij is the residual error term using the lme function in MATLAB (MATLAB Version: R2024a)g. We performed this LMR procedure for each pair of variables, and filtered for associations that were significant at p<0.05 after correction for multiple comparisons using Benjamini Hochberg procedure ( ).



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