linear mixed-effect models matlab r2018a Search Results


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MathWorks Inc bi-phasic nonlinear mixed effects (nlme) model nlmefit
Scatter plots showing the relations of the AMR variables to speech intelligibility (a–d) and speaking rate (e–h) in subjects with ALS. Circles correspond to data from subjects with a single-session recording; dots correspond to data from subjects with multiple-session (longitudinal) recordings. The lines correspond to the fit of the bi-phasic <t>NLME</t> models (a–d) and the LME models (e–h).
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Scatter plots showing the relations of the AMR variables to speech intelligibility (a–d) and speaking rate (e–h) in subjects with ALS. Circles correspond to data from subjects with a single-session recording; dots correspond to data from subjects with multiple-session (longitudinal) recordings. The lines correspond to the fit of the bi-phasic <t>NLME</t> models (a–d) and the LME models (e–h).
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Scatter plots showing the relations of the AMR variables to speech intelligibility (a–d) and speaking rate (e–h) in subjects with ALS. Circles correspond to data from subjects with a single-session recording; dots correspond to data from subjects with multiple-session (longitudinal) recordings. The lines correspond to the fit of the bi-phasic <t>NLME</t> models (a–d) and the LME models (e–h).
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Scatter plots showing the relations of the AMR variables to speech intelligibility (a–d) and speaking rate (e–h) in subjects with ALS. Circles correspond to data from subjects with a single-session recording; dots correspond to data from subjects with multiple-session (longitudinal) recordings. The lines correspond to the fit of the bi-phasic <t>NLME</t> models (a–d) and the LME models (e–h).
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Scatter plots showing the relations of the AMR variables to speech intelligibility (a–d) and speaking rate (e–h) in subjects with ALS. Circles correspond to data from subjects with a single-session recording; dots correspond to data from subjects with multiple-session (longitudinal) recordings. The lines correspond to the fit of the bi-phasic <t>NLME</t> models (a–d) and the LME models (e–h).
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MathWorks Inc matlab software r2018a
Scatter plots showing the relations of the AMR variables to speech intelligibility (a–d) and speaking rate (e–h) in subjects with ALS. Circles correspond to data from subjects with a single-session recording; dots correspond to data from subjects with multiple-session (longitudinal) recordings. The lines correspond to the fit of the bi-phasic <t>NLME</t> models (a–d) and the LME models (e–h).
Matlab Software R2018a, 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 showing the relations of the AMR variables to speech intelligibility (a–d) and speaking rate (e–h) in subjects with ALS. Circles correspond to data from subjects with a single-session recording; dots correspond to data from subjects with multiple-session (longitudinal) recordings. The lines correspond to the fit of the bi-phasic NLME models (a–d) and the LME models (e–h).

Journal: International journal of speech-language pathology

Article Title: Automatic extraction of abnormal lip movement features from the alternating motion rate (AMR) task in ALS

doi: 10.1080/17549507.2018.1485739

Figure Lengend Snippet: Scatter plots showing the relations of the AMR variables to speech intelligibility (a–d) and speaking rate (e–h) in subjects with ALS. Circles correspond to data from subjects with a single-session recording; dots correspond to data from subjects with multiple-session (longitudinal) recordings. The lines correspond to the fit of the bi-phasic NLME models (a–d) and the LME models (e–h).

Article Snippet: To assess behavioural changes during the progression of bulbar ALS, we stratified the early and late stages of bulbar ALS based on a bi-phasic nonlinear mixed effects (NLME) model ( nlmefit , MATLAB R2016a).

Techniques: