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functions mean, geomean, std, anovan, multcompare, corrcoef, fitlm, and aoctool  (MathWorks Inc)


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    MathWorks Inc functions mean, geomean, std, anovan, multcompare, corrcoef, fitlm, and aoctool
    Functions Mean, Geomean, Std, Anovan, Multcompare, Corrcoef, Fitlm, And Aoctool, 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/product/aoctool+function/pmc11468547-321-12-0
    Average 90 stars, based on 1 article reviews
    functions mean, geomean, std, anovan, multcompare, corrcoef, fitlm, and aoctool - by Bioz Stars, 2026-09
    90/100 stars

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    Related Articles

    other:

    Article Title: Markers of positive affect and brain state synchrony discriminate melancholic from non-melancholic depression using naturalistic stimuli.
    Article Snippet: The correlation between fMRI signal and mean facial muscle intensity was investigated using an interaction analysis with ‘aoctool’ in Matlab to identify putative differences in this relationship between melancholic and non-melancholic depression.

    Article Title: Effects of Salt Concentration on a Magnetic Nanoparticle-Based Aggregation Assay with a Tunable Dynamic Range.
    Article Snippet: We performed our ANOCOVA test with Matlab’s “aoctool” command with a 95% significance threshold.

    Article Title: Shape-Dependent Structural Order of Red Blood Cells
    Article Snippet: Statistics were computed using NumPy and SciPy Python packages., Analysis of covariance (ANCOVA) analysis was computed using aoctool in MATLAB.

    Article Title: Tissue‐Engineered Cochlear Fibrosis Model Links Complex Impedance to Fibrosis Formation for Cochlear Implant Patients
    Article Snippet: MATLAB's functions mean , geomean, std, anovan, multcompare, corrcoef, fitlm , and aoctool were used.

    Article Title: Effects of Salt Concentration on a Magnetic Nanoparticle-Based Aggregation Assay with a Tunable Dynamic Range.
    Article Snippet: Specifically, Matlab’s “aoctool” command was used to perform the ANCOVA testing.

    Article Title: Markers of positive affect and brain state synchrony discriminate melancholic from non-melancholic depression using naturalistic stimuli
    Article Snippet: The correlation between fMRI signal and mean facial muscle intensity was investigated using an interaction analysis with ‘ aoctool ’ in Matlab to identify putative differences in this relationship between melancholic and non-melancholic depression.

    Comparison:

    Article Title: Adaptive Window Method Based on FBCCA for Optimal SSVEP Recognition
    Article Snippet: .. ANCOVA and multiple comparison were implemented using aoctool and multcompare functions in MATLAB (MathWorks, Inc.,USA). ..

    Standard Deviation:

    Article Title: Shape-Dependent Structural Order of Red Blood Cells.
    Article Snippet: .. Statistics were computed using NumPy and SciPy Python packages.32,33 Analysis of covariance (ANCOVA) analysis was computed using aoctool in MATLAB.34 Plots were created using matplotlib.35 Error bars indicate the sample standard deviation. ..



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    A : 2PEF map of arterioles and venules (top) and of both vessel and GCaMP7f-expressing nNOS neurons (outlined in white, bottom). Vessels analyzed in B are circled in solid red or blue, and neurons are numbered (1,2,3) B : Arterioles, but not venules, dilate in response to whisker puffs, spontaneous whisking or motion (grooming). Representative Ca 2+ transients in neuron 1, 2, and 3 (middle). Overlay of normalized neural ensemble activity and arteriolar diameter changes highlighting the close correspondence between arteriolar and neural responses (bottom). C : Linear relationship between the magnitude of the ensemble activity and arteriolar dilatation in response to whisking or whisking and spontaneous motion. Notice that with whisking+motion the slope of the relationship is significantly greater than with whisking alone (multiple comparison of one-way analysis of <t>covariance</t> models). D : The distribution of correlation coefficients between arteriolar dilatation and nNOS Ca 2+ transients for individual neurons does not differ in the 3 mice studied (p>0.05; nested one-way ANOVA)(top). The strongest correlation is observed between ensemble activity and arteriolar dilatation (bottom). E : Representative arteriolar diameter changes relative to the timing of the peak Ca 2+ activity in individual neuron during 10 consecutive 5 sec whisker air puffs shown in B . Notice that in some neurons peak activity occur earlier than in other neurons. F : Average of ten raster plots in 3 mice showing early and late active nNOS neurons. Shading indicates standard deviation.
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    A : 2PEF map of arterioles and venules (top) and of both vessel and GCaMP7f-expressing nNOS neurons (outlined in white, bottom). Vessels analyzed in B are circled in solid red or blue, and neurons are numbered (1,2,3) B : Arterioles, but not venules, dilate in response to whisker puffs, spontaneous whisking or motion (grooming). Representative Ca 2+ transients in neuron 1, 2, and 3 (middle). Overlay of normalized neural ensemble activity and arteriolar diameter changes highlighting the close correspondence between arteriolar and neural responses (bottom). C : Linear relationship between the magnitude of the ensemble activity and arteriolar dilatation in response to whisking or whisking and spontaneous motion. Notice that with whisking+motion the slope of the relationship is significantly greater than with whisking alone (multiple comparison of one-way analysis of covariance models). D : The distribution of correlation coefficients between arteriolar dilatation and nNOS Ca 2+ transients for individual neurons does not differ in the 3 mice studied (p>0.05; nested one-way ANOVA)(top). The strongest correlation is observed between ensemble activity and arteriolar dilatation (bottom). E : Representative arteriolar diameter changes relative to the timing of the peak Ca 2+ activity in individual neuron during 10 consecutive 5 sec whisker air puffs shown in B . Notice that in some neurons peak activity occur earlier than in other neurons. F : Average of ten raster plots in 3 mice showing early and late active nNOS neurons. Shading indicates standard deviation.

    Journal: bioRxiv

    Article Title: Calcium transients in nNOS neurons underlie distinct phases of the neurovascular response to barrel cortex activation in awake mice

    doi: 10.1101/2022.10.03.510654

    Figure Lengend Snippet: A : 2PEF map of arterioles and venules (top) and of both vessel and GCaMP7f-expressing nNOS neurons (outlined in white, bottom). Vessels analyzed in B are circled in solid red or blue, and neurons are numbered (1,2,3) B : Arterioles, but not venules, dilate in response to whisker puffs, spontaneous whisking or motion (grooming). Representative Ca 2+ transients in neuron 1, 2, and 3 (middle). Overlay of normalized neural ensemble activity and arteriolar diameter changes highlighting the close correspondence between arteriolar and neural responses (bottom). C : Linear relationship between the magnitude of the ensemble activity and arteriolar dilatation in response to whisking or whisking and spontaneous motion. Notice that with whisking+motion the slope of the relationship is significantly greater than with whisking alone (multiple comparison of one-way analysis of covariance models). D : The distribution of correlation coefficients between arteriolar dilatation and nNOS Ca 2+ transients for individual neurons does not differ in the 3 mice studied (p>0.05; nested one-way ANOVA)(top). The strongest correlation is observed between ensemble activity and arteriolar dilatation (bottom). E : Representative arteriolar diameter changes relative to the timing of the peak Ca 2+ activity in individual neuron during 10 consecutive 5 sec whisker air puffs shown in B . Notice that in some neurons peak activity occur earlier than in other neurons. F : Average of ten raster plots in 3 mice showing early and late active nNOS neurons. Shading indicates standard deviation.

    Article Snippet: To evaluate statistical differences between the linear correlations of two data sets, we generated one-way analysis of covariance models (Matlab function: aoctool) and ran multiple comparison test (Tukey-Kramer) of the group means (Matlab function: multcompare).

    Techniques: Expressing, Whisker Assay, Activity Assay, Comparison, Standard Deviation