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multivariable linear regression model test  (MathWorks Inc)


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    MathWorks Inc multivariable linear regression model test
    <t>Multivariable</t> linear regression model (see “Materials and Methods” section). Fit (solid black line) and the 95% confidence bounds (black dashed lines) of the constant (number of BDA-labeled boutons) vs. the other variables (PD symptoms and TH+ loss in SNpc) in the model. The multi variables are “partialed out” but not the constant term. Therefore, the X-abscissa represents the combined independent variables (PD symptoms and TH+ loss) adjusted by the model. The model has an explanatory power (positive slope: y = 9.298* x ; R 2 = 0.821; adjusted R 2 = 0.731; p -value = 0.0117). Three clusters (ovals) appear: (1) the highest TH+ loss and motor impairment (yellow); (2) the lowest loss of TH+ neurons and motor impairment (purple) and (3) the intact animal cluster (gray) without dopaminergic loss nor PD symptoms.
    Multivariable Linear Regression Model Test, 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/multivariable linear regression model test/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    multivariable linear regression model test - by Bioz Stars, 2026-04
    90/100 stars

    Images

    1) Product Images from "Cortical Projection From the Premotor or Primary Motor Cortex to the Subthalamic Nucleus in Intact and Parkinsonian Adult Macaque Monkeys: A Pilot Tracing Study"

    Article Title: Cortical Projection From the Premotor or Primary Motor Cortex to the Subthalamic Nucleus in Intact and Parkinsonian Adult Macaque Monkeys: A Pilot Tracing Study

    Journal: Frontiers in Neural Circuits

    doi: 10.3389/fncir.2020.528993

    Multivariable linear regression model (see “Materials and Methods” section). Fit (solid black line) and the 95% confidence bounds (black dashed lines) of the constant (number of BDA-labeled boutons) vs. the other variables (PD symptoms and TH+ loss in SNpc) in the model. The multi variables are “partialed out” but not the constant term. Therefore, the X-abscissa represents the combined independent variables (PD symptoms and TH+ loss) adjusted by the model. The model has an explanatory power (positive slope: y = 9.298* x ; R 2 = 0.821; adjusted R 2 = 0.731; p -value = 0.0117). Three clusters (ovals) appear: (1) the highest TH+ loss and motor impairment (yellow); (2) the lowest loss of TH+ neurons and motor impairment (purple) and (3) the intact animal cluster (gray) without dopaminergic loss nor PD symptoms.
    Figure Legend Snippet: Multivariable linear regression model (see “Materials and Methods” section). Fit (solid black line) and the 95% confidence bounds (black dashed lines) of the constant (number of BDA-labeled boutons) vs. the other variables (PD symptoms and TH+ loss in SNpc) in the model. The multi variables are “partialed out” but not the constant term. Therefore, the X-abscissa represents the combined independent variables (PD symptoms and TH+ loss) adjusted by the model. The model has an explanatory power (positive slope: y = 9.298* x ; R 2 = 0.821; adjusted R 2 = 0.731; p -value = 0.0117). Three clusters (ovals) appear: (1) the highest TH+ loss and motor impairment (yellow); (2) the lowest loss of TH+ neurons and motor impairment (purple) and (3) the intact animal cluster (gray) without dopaminergic loss nor PD symptoms.

    Techniques Used: Labeling



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    multivariable linear regression model test  (MathWorks Inc)
    90
    MathWorks Inc multivariable linear regression model test
    <t>Multivariable</t> linear regression model (see “Materials and Methods” section). Fit (solid black line) and the 95% confidence bounds (black dashed lines) of the constant (number of BDA-labeled boutons) vs. the other variables (PD symptoms and TH+ loss in SNpc) in the model. The multi variables are “partialed out” but not the constant term. Therefore, the X-abscissa represents the combined independent variables (PD symptoms and TH+ loss) adjusted by the model. The model has an explanatory power (positive slope: y = 9.298* x ; R 2 = 0.821; adjusted R 2 = 0.731; p -value = 0.0117). Three clusters (ovals) appear: (1) the highest TH+ loss and motor impairment (yellow); (2) the lowest loss of TH+ neurons and motor impairment (purple) and (3) the intact animal cluster (gray) without dopaminergic loss nor PD symptoms.
    Multivariable Linear Regression Model Test, 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/multivariable linear regression model test/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    multivariable linear regression model test - by Bioz Stars, 2026-04
    90/100 stars
    		  Buy from Supplier

    Image Search Results


    Multivariable linear regression model (see “Materials and Methods” section). Fit (solid black line) and the 95% confidence bounds (black dashed lines) of the constant (number of BDA-labeled boutons) vs. the other variables (PD symptoms and TH+ loss in SNpc) in the model. The multi variables are “partialed out” but not the constant term. Therefore, the X-abscissa represents the combined independent variables (PD symptoms and TH+ loss) adjusted by the model. The model has an explanatory power (positive slope: y = 9.298* x ; R 2 = 0.821; adjusted R 2 = 0.731; p -value = 0.0117). Three clusters (ovals) appear: (1) the highest TH+ loss and motor impairment (yellow); (2) the lowest loss of TH+ neurons and motor impairment (purple) and (3) the intact animal cluster (gray) without dopaminergic loss nor PD symptoms.

    Journal: Frontiers in Neural Circuits

    Article Title: Cortical Projection From the Premotor or Primary Motor Cortex to the Subthalamic Nucleus in Intact and Parkinsonian Adult Macaque Monkeys: A Pilot Tracing Study

    doi: 10.3389/fncir.2020.528993

    Figure Lengend Snippet: Multivariable linear regression model (see “Materials and Methods” section). Fit (solid black line) and the 95% confidence bounds (black dashed lines) of the constant (number of BDA-labeled boutons) vs. the other variables (PD symptoms and TH+ loss in SNpc) in the model. The multi variables are “partialed out” but not the constant term. Therefore, the X-abscissa represents the combined independent variables (PD symptoms and TH+ loss) adjusted by the model. The model has an explanatory power (positive slope: y = 9.298* x ; R 2 = 0.821; adjusted R 2 = 0.731; p -value = 0.0117). Three clusters (ovals) appear: (1) the highest TH+ loss and motor impairment (yellow); (2) the lowest loss of TH+ neurons and motor impairment (purple) and (3) the intact animal cluster (gray) without dopaminergic loss nor PD symptoms.

    Article Snippet: To assess the relationship between the number of BDA-labeled boutons with the interaction between motor impairment (PD symptoms based on manual dexterity in the modified-Brinkman board task post-ANCE transplantation (see above) and dopaminergic (tyrosine hydroxylase positive (TH+) neurons) loss in the substantia nigra pars compacta (SNpc), we performed a multivariable linear regression model test (MATLAB R2017b, function “fitlm”; Contestabile et al., ).

    Techniques: Labeling