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pearson correlation coefficient (r) with  (MathWorks Inc)


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    MathWorks Inc pearson correlation coefficient (r) with
    Pearson Correlation Coefficient (R) With, 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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    Average 90 stars, based on 1 article reviews
    pearson correlation coefficient (r) with - by Bioz Stars, 2026-09
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    Article Title: Quantification correction for free-breathing myocardial T 1ρ mapping in mice using a recursively derived description of a T 1ρ * relaxation pathway
    Article Snippet: Linear regression was performed for correlation analysis of measured relaxation times with recorded recovery times.Linear regression was performed for correlation analysis of measured relaxation times with recorded recovery times.. The measure used was the Pearson correlation coefficient r (The MathWorks, Statistics and Machine Learning Toolbox).. Continuous variables are expressed as mean ± standard deviation.Continuous variables are expressed as mean ± standard deviation.

    Article Title: A fair and EMG-validated comparison of recruitment criteria, musculotendon models and muscle coordination strategies, for the inverse-dynamics based optimization of muscle forces during gait
    Article Snippet: smooth and continuous during gait, the optimal solution from the previous time frame is used as the initial guess for the current time frame [ ]. .. Matching between estimated muscle activations and EMG was quantified via cross-correlation using the Pearson correlation coefficient r (Matlab’s function corrcoef ) with a maximum time delay of 150 ms [ ]. .. The correlation coefficient r was chosen to compare muscle activations and EMG data so as to focus on shape rather than on magnitude discrepancies, as

    Article Title: Do Muscle Synergies Improve Optimization Prediction of Muscle Activations During Gait?
    Article Snippet: matrix factorization (NMF) was performed on the SO activations, and then muscle activation estimates were constructed from the synergies. .. For each approach, inverse-dynamics joint moment matching was quantified using the total variance account (VAF), whereas EMG matching was quantified via cross correlation using the Pearson correlation coefficient r (MATLAB's function corrcoef ) with a maximum time delay of 100 ms (Shourijeh et al., ). .. The correlation coefficient r was chosen to compare muscle activations and EMG data so as to focus on shape differences (between the activation patter



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    a , b Scatterplot showing the relationship between gene-level alteration frequencies in ctDNA and archival tissues from ( a ) 141 patients who received prior anti-VEGF therapies, and ( b )113 patients who received prior anti-EGFR therapies. The effect size was estimated using Pearson’s correlation coefficient(r) calculated in GraphPad Prism, and the coefficient of determination (r 2 ), representing the proportion of variance explained by the relationship, is displayed on the scatter plot. c Comparison of percentage of patients with emerging alterations between patients with prior anti-EGFR therapies and those with prior anti-VEGF therapies. Alterations that were absent from tumor tissue samples but detected in plasma samples were defined as emerging alterations. (All genes with at least one emerging alteration listed). Only known and likely oncogenic alterations in each gene were considered for the analysis. P- value was calculated using a two-tailed Fisher’s exact test to compare the percentage of patients with emerging alterations between those who received anti-EGFR therapies and those who received anti-VEGF therapies. Source data are provided as a Source Data file.

    Journal: Nature Communications

    Article Title: Ligand-activated EGFR/MAPK signaling but not PI3K, are key resistance mechanisms to EGFR-therapy in colorectal cancer

    doi: 10.1038/s41467-025-59588-3

    Figure Lengend Snippet: a , b Scatterplot showing the relationship between gene-level alteration frequencies in ctDNA and archival tissues from ( a ) 141 patients who received prior anti-VEGF therapies, and ( b )113 patients who received prior anti-EGFR therapies. The effect size was estimated using Pearson’s correlation coefficient(r) calculated in GraphPad Prism, and the coefficient of determination (r 2 ), representing the proportion of variance explained by the relationship, is displayed on the scatter plot. c Comparison of percentage of patients with emerging alterations between patients with prior anti-EGFR therapies and those with prior anti-VEGF therapies. Alterations that were absent from tumor tissue samples but detected in plasma samples were defined as emerging alterations. (All genes with at least one emerging alteration listed). Only known and likely oncogenic alterations in each gene were considered for the analysis. P- value was calculated using a two-tailed Fisher’s exact test to compare the percentage of patients with emerging alterations between those who received anti-EGFR therapies and those who received anti-VEGF therapies. Source data are provided as a Source Data file.

    Article Snippet: The effect size was estimated using Pearson’s correlation coefficient(r) calculated in GraphPad Prism, and the coefficient of determination (r 2 ), representing the proportion of variance explained by the relationship, is displayed on the scatter plot. c Comparison of percentage of patients with emerging alterations between patients with prior anti-EGFR therapies and those with prior anti-VEGF therapies.

    Techniques: Comparison, Clinical Proteomics, Two Tailed Test