lme function matlab r2014b Search Results


lme model  (MathWorks Inc)
90
MathWorks Inc lme model
Scatter plots of the relation between speaking rate and each <t>subsystem</t> <t>predictor</t> accounting for time and subject effects: (a) respiratory, (b) phonatory, (c) articulatory, and (d) resonatory. On the x -axis is the subsystem predictor adjusted for time, which is the combination of each subsystem predictor and the effect of time on speaking rate. On the y -axis is the normalized speaking rate derived by subtracting the subject-dependent random effect from speaking rate. The lines are the linear fits based on the <t>LME</t> models.
Lme 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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lme function matlab r2014b  (MathWorks Inc)
90
MathWorks Inc lme function matlab r2014b
Scatter plots of the relation between speaking rate and each <t>subsystem</t> <t>predictor</t> accounting for time and subject effects: (a) respiratory, (b) phonatory, (c) articulatory, and (d) resonatory. On the x -axis is the subsystem predictor adjusted for time, which is the combination of each subsystem predictor and the effect of time on speaking rate. On the y -axis is the normalized speaking rate derived by subtracting the subject-dependent random effect from speaking rate. The lines are the linear fits based on the <t>LME</t> models.
Lme Function Matlab R2014b, 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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lme function in matlab r2019b  (MathWorks Inc)
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MathWorks Inc lme function in matlab r2019b
Scatter plots of the relation between speaking rate and each <t>subsystem</t> <t>predictor</t> accounting for time and subject effects: (a) respiratory, (b) phonatory, (c) articulatory, and (d) resonatory. On the x -axis is the subsystem predictor adjusted for time, which is the combination of each subsystem predictor and the effect of time on speaking rate. On the y -axis is the normalized speaking rate derived by subtracting the subject-dependent random effect from speaking rate. The lines are the linear fits based on the <t>LME</t> models.
Lme Function In Matlab R2019b, 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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linear mixed effect models (lme) with matlab r2016b  (MathWorks Inc)
90
MathWorks Inc linear mixed effect models (lme) with matlab r2016b
Scatter plots of the relation between speaking rate and each <t>subsystem</t> <t>predictor</t> accounting for time and subject effects: (a) respiratory, (b) phonatory, (c) articulatory, and (d) resonatory. On the x -axis is the subsystem predictor adjusted for time, which is the combination of each subsystem predictor and the effect of time on speaking rate. On the y -axis is the normalized speaking rate derived by subtracting the subject-dependent random effect from speaking rate. The lines are the linear fits based on the <t>LME</t> models.
Linear Mixed Effect Models (Lme) With Matlab R2016b, 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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matlab r2014b  (MathWorks Inc)
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MathWorks Inc matlab r2014b
Scatter plots of the relation between speaking rate and each <t>subsystem</t> <t>predictor</t> accounting for time and subject effects: (a) respiratory, (b) phonatory, (c) articulatory, and (d) resonatory. On the x -axis is the subsystem predictor adjusted for time, which is the combination of each subsystem predictor and the effect of time on speaking rate. On the y -axis is the normalized speaking rate derived by subtracting the subject-dependent random effect from speaking rate. The lines are the linear fits based on the <t>LME</t> models.
Matlab R2014b, 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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fitlme function  (MathWorks Inc)
90
MathWorks Inc fitlme function
Scatter plots of the relation between speaking rate and each <t>subsystem</t> <t>predictor</t> accounting for time and subject effects: (a) respiratory, (b) phonatory, (c) articulatory, and (d) resonatory. On the x -axis is the subsystem predictor adjusted for time, which is the combination of each subsystem predictor and the effect of time on speaking rate. On the y -axis is the normalized speaking rate derived by subtracting the subject-dependent random effect from speaking rate. The lines are the linear fits based on the <t>LME</t> models.
Fitlme 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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r2013b  (MathWorks Inc)
90
MathWorks Inc r2013b
Scatter plots of the relation between speaking rate and each <t>subsystem</t> <t>predictor</t> accounting for time and subject effects: (a) respiratory, (b) phonatory, (c) articulatory, and (d) resonatory. On the x -axis is the subsystem predictor adjusted for time, which is the combination of each subsystem predictor and the effect of time on speaking rate. On the y -axis is the normalized speaking rate derived by subtracting the subject-dependent random effect from speaking rate. The lines are the linear fits based on the <t>LME</t> models.
R2013b, 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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matlab r2014 software  (MathWorks Inc)
90
MathWorks Inc matlab r2014 software
Scatter plots of the relation between speaking rate and each <t>subsystem</t> <t>predictor</t> accounting for time and subject effects: (a) respiratory, (b) phonatory, (c) articulatory, and (d) resonatory. On the x -axis is the subsystem predictor adjusted for time, which is the combination of each subsystem predictor and the effect of time on speaking rate. On the y -axis is the normalized speaking rate derived by subtracting the subject-dependent random effect from speaking rate. The lines are the linear fits based on the <t>LME</t> models.
Matlab R2014 Software, 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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12.5 package  (TIBCO)
90
TIBCO 12.5 package
Scatter plots of the relation between speaking rate and each <t>subsystem</t> <t>predictor</t> accounting for time and subject effects: (a) respiratory, (b) phonatory, (c) articulatory, and (d) resonatory. On the x -axis is the subsystem predictor adjusted for time, which is the combination of each subsystem predictor and the effect of time on speaking rate. On the y -axis is the normalized speaking rate derived by subtracting the subject-dependent random effect from speaking rate. The lines are the linear fits based on the <t>LME</t> models.
12.5 Package, supplied by TIBCO, 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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fitlme function in matlab r2016b  (MathWorks Inc)
90
MathWorks Inc fitlme function in matlab r2016b
Scatter plots of the relation between speaking rate and each <t>subsystem</t> <t>predictor</t> accounting for time and subject effects: (a) respiratory, (b) phonatory, (c) articulatory, and (d) resonatory. On the x -axis is the subsystem predictor adjusted for time, which is the combination of each subsystem predictor and the effect of time on speaking rate. On the y -axis is the normalized speaking rate derived by subtracting the subject-dependent random effect from speaking rate. The lines are the linear fits based on the <t>LME</t> models.
Fitlme Function In Matlab R2016b, 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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linear mixed effect model  (MathWorks Inc)
90
MathWorks Inc linear mixed effect model
Scatter plots of the relation between speaking rate and each <t>subsystem</t> <t>predictor</t> accounting for time and subject effects: (a) respiratory, (b) phonatory, (c) articulatory, and (d) resonatory. On the x -axis is the subsystem predictor adjusted for time, which is the combination of each subsystem predictor and the effect of time on speaking rate. On the y -axis is the normalized speaking rate derived by subtracting the subject-dependent random effect from speaking rate. The lines are the linear fits based on the <t>LME</t> models.
Linear Mixed Effect 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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Image Search Results


Scatter plots of the relation between speaking rate and each subsystem predictor accounting for time and subject effects: (a) respiratory, (b) phonatory, (c) articulatory, and (d) resonatory. On the x -axis is the subsystem predictor adjusted for time, which is the combination of each subsystem predictor and the effect of time on speaking rate. On the y -axis is the normalized speaking rate derived by subtracting the subject-dependent random effect from speaking rate. The lines are the linear fits based on the LME models.

Journal: Behavioural Neurology

Article Title: Predicting Early Bulbar Decline in Amyotrophic Lateral Sclerosis: A Speech Subsystem Approach

doi: 10.1155/2015/183027

Figure Lengend Snippet: Scatter plots of the relation between speaking rate and each subsystem predictor accounting for time and subject effects: (a) respiratory, (b) phonatory, (c) articulatory, and (d) resonatory. On the x -axis is the subsystem predictor adjusted for time, which is the combination of each subsystem predictor and the effect of time on speaking rate. On the y -axis is the normalized speaking rate derived by subtracting the subject-dependent random effect from speaking rate. The lines are the linear fits based on the LME models.

Article Snippet: To combine the principal components of each subsystem into a single predictor of the overall bulbar decline, we applied an LME model ( fitlme , MATLAB R2013b) that predicted speaking rate as a function of the principal components of each subsystem and time (i.e., days after diagnosis) controlling for the subject effect.

Techniques: Derivative Assay

Fixed effects and R 2 values for the LME models of the four subsystems (respiratory, phonatory, articulatory, and resonatory).

Journal: Behavioural Neurology

Article Title: Predicting Early Bulbar Decline in Amyotrophic Lateral Sclerosis: A Speech Subsystem Approach

doi: 10.1155/2015/183027

Figure Lengend Snippet: Fixed effects and R 2 values for the LME models of the four subsystems (respiratory, phonatory, articulatory, and resonatory).

Article Snippet: To combine the principal components of each subsystem into a single predictor of the overall bulbar decline, we applied an LME model ( fitlme , MATLAB R2013b) that predicted speaking rate as a function of the principal components of each subsystem and time (i.e., days after diagnosis) controlling for the subject effect.

Techniques: