fitglme Search Results


general linear model matlab 2019b fitglm  (MathWorks Inc)
90
MathWorks Inc general linear model matlab 2019b fitglm
General Linear Model Matlab 2019b Fitglm, 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/result/general linear model matlab 2019b fitglm/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
general linear model matlab 2019b fitglm - by Bioz Stars, 2026-03
90/100 stars
  Buy from Supplier
logistic regression model  (MathWorks Inc)
90
MathWorks Inc logistic regression model
Logistic Regression 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
https://www.bioz.com/result/logistic regression model/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
logistic regression model - by Bioz Stars, 2026-03
90/100 stars
  Buy from Supplier
fitglme function  (MathWorks Inc)
90
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
https://www.bioz.com/result/fitglme function/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
fitglme function - by Bioz Stars, 2026-03
90/100 stars
  Buy from Supplier
generalized linear models (glms) assuming binomial distributions and using the logit link function  (MathWorks Inc)
90
MathWorks Inc generalized linear models (glms) assuming binomial distributions and using the logit link function
Generalized Linear Models (Glms) Assuming Binomial Distributions And Using The Logit 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/result/generalized linear models (glms) assuming binomial distributions and using the logit link function/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
generalized linear models (glms) assuming binomial distributions and using the logit link function - by Bioz Stars, 2026-03
90/100 stars
  Buy from Supplier
generalized linear model fitglm function  (MathWorks Inc)
90
MathWorks Inc generalized linear model fitglm function
Generalized Linear Model Fitglm 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/result/generalized linear model fitglm function/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
generalized linear model fitglm function - by Bioz Stars, 2026-03
90/100 stars
  Buy from Supplier
generalized linear mixed-effects models (glmms) in  (MathWorks Inc)
90
MathWorks Inc generalized linear mixed-effects models (glmms) in
Generalized Linear Mixed Effects Models (Glmms) 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/result/generalized linear mixed-effects models (glmms) in/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
generalized linear mixed-effects models (glmms) in - by Bioz Stars, 2026-03
90/100 stars
  Buy from Supplier
general linear mixed effects models using matlab's fitglme  (MathWorks Inc)
90
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
https://www.bioz.com/result/general linear mixed effects models using matlab's fitglme/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
general linear mixed effects models using matlab's fitglme - by Bioz Stars, 2026-03
90/100 stars
  Buy from Supplier
fitglm function  (MathWorks Inc)
90
MathWorks Inc fitglm function
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).
Fitglm 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/result/fitglm function/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
fitglm function - by Bioz Stars, 2026-03
90/100 stars
  Buy from Supplier
fitglme from matlab  (MathWorks Inc)
90
MathWorks Inc fitglme from matlab
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).
Fitglme From Matlab, 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/result/fitglme from matlab/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
fitglme from matlab - by Bioz Stars, 2026-03
90/100 stars
  Buy from Supplier
fitglm  (MathWorks Inc)
90
MathWorks Inc fitglm
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).
Fitglm, 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/result/fitglm/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
fitglm - by Bioz Stars, 2026-03
90/100 stars
  Buy from Supplier

Image Search Results


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