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generalized linear models with a logit link function using matlab’s fitglme function  (MathWorks Inc)


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    MathWorks Inc generalized linear models with a logit link function using matlab’s fitglme function
    Generalized Linear Models With A Logit Link Function Using Matlab’s Fitglme Function, 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/general+linear+model+function/pm40478648-118-12-11
    Average 90 stars, based on 1 article reviews
    generalized linear models with a logit link function using matlab’s fitglme function - by Bioz Stars, 2026-09
    90/100 stars

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    Article Title: Supporting Information A Computational Account of Transsaccadic Attentional Allocation Based on Visual Gain Fields
    Article Snippet: The model was fit using MATLAB’s fitglme() function.

    Article Title: Neurophysiological response and connectivity changes in the STN with a month-long exercise intervention
    Article Snippet: The model was fitted using MATLAB’s fitglme function that uses maximum likelihood estimation for parameter estimation.

    Article Title: Improved Genotype Inference Reveals Cis- and Trans-Driven Variation in the Loss-of-Heterozygosity Rates in Yeast
    Article Snippet: We fit all generalized linear mixed effects models using the fitglme function in Matlab R2024b with the option of approximating the log-likelihood using Laplace’s method.

    Article Title: Behavioral and computational signatures of reinforcement learning and confidence biases in gambling disorder.
    Article Snippet: We used generalized linear models with a logit link function using MATLAB’s fitglme function.

    Article Title: Manipulating memory processing during sleep to explore the critical duration of reactivation events.
    Article Snippet: Data was fitted to a generalized linear mixed regression model using the fitglme function in MATLAB.

    Article Title: Joint contact forces during barefoot, minimal and conventional shod running are highly individual
    Article Snippet: The data were fitted using MATLAB’s fitglme function, selecting the maximum pseudo-likelihood fit method, effects coding, normal distribution family with identity link function, and the following formula \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\begin{aligned} & {\texttt {y}} \sim {\texttt {shoe}} *{\texttt {speed}} + (1|{\texttt {stride}}) + (1|{\texttt {stride:subject}}) \end{aligned}$$\end{document} y ∼ shoe ∗ speed + ( 1 | stride ) + ( 1 | stride : subject ) where y is the dependent variable.

    Article Title: Associating everything with everything else, all at once: Semantic associations facilitate visual working memory formation for real-world objects.
    Article Snippet: Model fitting was implemented via the fitglme function in MATLAB.

    Article Title: Joint contact forces during barefoot, minimal and conventional shod running are highly individual.
    Article Snippet: The data were fitted using MATLAB’s fitglme function, selecting the maximum pseudo-likelihood fit method, effects coding, normal distribution family with identity link function, and the following formula y ∼ shoe ∗ speed + (1|stride) + (1|stride:subject) where y is the dependent variable.



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