generalized linear mixed-effects model fitglme function Search Results


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MathWorks Inc general linear mixed effects models using matlab's fitglme
Effect sizes from a <t>general</t> <t>linear</t> <t>mixed</t> model (see “Methods”) estimating impact of stimulus category ( a ), choice ( b – d ), and action ( e – h ) on MEG power, in different regions and frequency bands. a Effect of current stimulus category on gamma (top) and alpha (bottom) power during test stimulus ( n = 60). b As a , but for effect of previous choice in the reference interval. c As b , but for test stimulus interval. d Comparison of choice history signals between alternators ( n = 25; orange) and repeaters ( n = 34; purple). Group effect = 0.55328, CI [0.19342, 0.91314], p = 0.00258. e Effect of current action preparation on gamma (top) and beta (bottom) power during test stimulus ( n = 60). f As e , but for effect of previous action during reference interval. g As f , but for the test interval. h Comparison of action history signals between alternators ( n = 25; orange) and repeaters ( n = 34; purple). Data are shown as average fixed effect size +/− 95% confidence intervals; *0.01 < p < 0.05 (no such effect present); **0.001 < p < 0.01; *** p < 0.001; filled markers, p < 0.05 (all p values FDR corrected).
General Linear Mixed Effects Models Using Matlab's Fitglme, 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
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MathWorks Inc fitglme function

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
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MathWorks Inc mixed-effects logistic regression

Mixed Effects Logistic Regression, 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
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MathWorks Inc logistic mixed-effect models (fitglme)

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MathWorks Inc linear mixed-effects models

Linear Mixed Effects Models, 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
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MathWorks Inc mixed effects glme model

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MathWorks Inc generalized linear mixed-effects logistic regression model fitglme
<t> Mixed-Effects Logistic Regression Model </t> Summary
Generalized Linear Mixed Effects Logistic Regression Model Fitglme, 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
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MathWorks Inc generalised linear mixed-effects model
<t> Mixed-Effects Logistic Regression Model </t> Summary
Generalised Linear Mixed Effects Model, 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
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MathWorks Inc fitglme
<t> Mixed-Effects Logistic Regression Model </t> Summary
Fitglme, 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
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MathWorks Inc matlab function fitglme
<t> Mixed-Effects Logistic Regression Model </t> Summary
Matlab Function Fitglme, 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
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Effect sizes from a general linear mixed model (see “Methods”) estimating impact of stimulus category ( a ), choice ( b – d ), and action ( e – h ) on MEG power, in different regions and frequency bands. a Effect of current stimulus category on gamma (top) and alpha (bottom) power during test stimulus ( n = 60). b As a , but for effect of previous choice in the reference interval. c As b , but for test stimulus interval. d Comparison of choice history signals between alternators ( n = 25; orange) and repeaters ( n = 34; purple). Group effect = 0.55328, CI [0.19342, 0.91314], p = 0.00258. e Effect of current action preparation on gamma (top) and beta (bottom) power during test stimulus ( n = 60). f As e , but for effect of previous action during reference interval. g As f , but for the test interval. h Comparison of action history signals between alternators ( n = 25; orange) and repeaters ( n = 34; purple). Data are shown as average fixed effect size +/− 95% confidence intervals; *0.01 < p < 0.05 (no such effect present); **0.001 < p < 0.01; *** p < 0.001; filled markers, p < 0.05 (all p values FDR corrected).

Journal: Nature Communications

Article Title: Persistent activity in human parietal cortex mediates perceptual choice repetition bias

doi: 10.1038/s41467-022-33237-5

Figure Lengend Snippet: Effect sizes from a general linear mixed model (see “Methods”) estimating impact of stimulus category ( a ), choice ( b – d ), and action ( e – h ) on MEG power, in different regions and frequency bands. a Effect of current stimulus category on gamma (top) and alpha (bottom) power during test stimulus ( n = 60). b As a , but for effect of previous choice in the reference interval. c As b , but for test stimulus interval. d Comparison of choice history signals between alternators ( n = 25; orange) and repeaters ( n = 34; purple). Group effect = 0.55328, CI [0.19342, 0.91314], p = 0.00258. e Effect of current action preparation on gamma (top) and beta (bottom) power during test stimulus ( n = 60). f As e , but for effect of previous action during reference interval. g As f , but for the test interval. h Comparison of action history signals between alternators ( n = 25; orange) and repeaters ( n = 34; purple). Data are shown as average fixed effect size +/− 95% confidence intervals; *0.01 < p < 0.05 (no such effect present); **0.001 < p < 0.01; *** p < 0.001; filled markers, p < 0.05 (all p values FDR corrected).

Article Snippet: We used general linear mixed effects models (GLMEs, using Matlab’s fitglme ) to quantify the effect of choice history on single-trial power modulation values across all source-level ROIs, frequency ranges and the above-defined time windows.

Techniques: Comparison

Time-resolved effect sizes from a general linear mixed model (see “Methods”), separately for both subgroups. a Effect of current and previous choice on IPS2/3 gamma-band activity. b Effect of current and previous choice on IPS0/1 alpha-band activity. c Effect of current and previous action on motor lateralization (pooled signal from M1, PMd/v, IPS/PCeS) in the beta-band. Lower markers indicate timepoints where the fixed effect is significantly different within each group, or between groups ( p < 0.05, FDR-corrected). Data are shown as average fixed effect size +/− 95% confidence intervals.

Journal: Nature Communications

Article Title: Persistent activity in human parietal cortex mediates perceptual choice repetition bias

doi: 10.1038/s41467-022-33237-5

Figure Lengend Snippet: Time-resolved effect sizes from a general linear mixed model (see “Methods”), separately for both subgroups. a Effect of current and previous choice on IPS2/3 gamma-band activity. b Effect of current and previous choice on IPS0/1 alpha-band activity. c Effect of current and previous action on motor lateralization (pooled signal from M1, PMd/v, IPS/PCeS) in the beta-band. Lower markers indicate timepoints where the fixed effect is significantly different within each group, or between groups ( p < 0.05, FDR-corrected). Data are shown as average fixed effect size +/− 95% confidence intervals.

Article Snippet: We used general linear mixed effects models (GLMEs, using Matlab’s fitglme ) to quantify the effect of choice history on single-trial power modulation values across all source-level ROIs, frequency ranges and the above-defined time windows.

Techniques: Activity Assay

Journal: iScience

Article Title: Pretrial predictors of conflict response efficacy in the human prefrontal cortex

doi: 10.1016/j.isci.2023.108047

Figure Lengend Snippet:

Article Snippet: fitGLME function for computing generalized linear mixed effect models , MATLAB, the Mathworks, Inc , .

Techniques: Software

 Mixed-Effects Logistic Regression Model  Summary

Journal: Translational Vision Science & Technology

Article Title: Comparing Objective Perimetry, Matrix Perimetry, and Regional Retinal Thickness in Mild Diabetic Macular Edema

doi: 10.1167/tvst.10.13.32

Figure Lengend Snippet: Mixed-Effects Logistic Regression Model Summary

Article Snippet: We fitted a generalized linear mixed-effects logistic regression model ( fitglme in MATLAB) to account for the effects of multiple comparisons, eyes, and repeats being nested within participants.

Techniques: