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generalised linear mixed effects model (glmm) with a probit link function  (MathWorks Inc)


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    MathWorks Inc generalised linear mixed effects model (glmm) with a probit link function
    Generalised Linear Mixed Effects Model (Glmm) With A Probit Link 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/generalised+linear+model+function/pm32836059-237-24-29
    Average 90 stars, based on 1 article reviews
    generalised linear mixed effects model (glmm) with a probit link function - by Bioz Stars, 2026-10
    90/100 stars

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    Article Title: Opposite regulation of medullary pain–related projection neuron excitability in acute and chronic pain
    Article Snippet: For the statistical analysis of eye wipes over time ( , middle), we fitted a linear mixed-effects model (MATLAB, function fitlme) using group, day, and the interaction of them for fixed effects and mouse ID for a random effect.

    Article Title: Error-driven changes in hippocampal representations accompany flexible re-learning
    Article Snippet: We fit the model across the dataset of animals and sessions using a mixed effects model in MATLAB, including the random effect of animal ID.

    Article Title: Kinetic modeling of 18 F-PI-2620 binding in the brain using an image-derived input function with total-body PET.
    Article Snippet: A linear mixed-effects model (using MATLAB’s fitlme function) was employed to investigate the relationship between kinetic measures (quantified with 90-minute data) and ROIs, accounting for random subject variance and the fixed effect of age.

    Article Title: Mapping the landscape of social behavior.
    Article Snippet: Specifically, we fit a linear mixed effects model (LME, Matlab function fitlme()) to observations (e.g., the usage of a specific cluster in each recording session) given a fixed effect for experimental group (e.g., ASD KO vs. WT littermate) and a random effect for intercept grouped by subject identity.

    Article Title: Alzheimer's disease patient-derived high-molecular-weight tau impairs bursting in hippocampal neurons.
    Article Snippet: A linear mixed effects model was thus deployed (MATLAB function ‘fitlme’) with genotype as a fixed effect and mouse/subject identification code as a random effect.

    Article Title: Focused Ultrasound Modulates Dopamine in a Mesolimbic Reward Circuit
    Article Snippet: A generalized linear mixed‐effects model was applied using MATLAB.

    Article Title: The discharge characteristics of motor units innervating functionally paralyzed muscles.
    Article Snippet: To assess the statistical differences between the groups, we used a generalized linear mixed-effects model (glmer, MATLAB) according to the equation: variable of interest task group þ (1 j participant), group and tasks were considered as fixed-effects, and the participants as a random effect.

    Article Title: An adaptable, reusable, and light implant for chronic Neuropixels probes
    Article Snippet: To estimate the effect of repeated probe use, U , and antero-posterior and medio-lateral insertion coordinates ( Y and X ) on a variable of interest (e.g. the percentage change in unit count, or the RMS values) across days, we used a linear mixed-effects model (using the MATLAB fitlme function): P ∼ 1 + Y + X + U + ( 1 | p r o b e I D ) + ( U − 1 | p r o b e I D ) Here, P is the response variable, Y , X , and U are fixed effect terms, and probeID (the probe identity) is the single grouping variable.



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