Search alternatives:
significantly predicted » significantly reduced (Expand Search), significantly reduce (Expand Search), significant predictor (Expand Search)
predicted increases » projected increase (Expand Search), predictably increase (Expand Search)
linear decrease » linear increase (Expand Search)
teer decrease » mean decrease (Expand Search), greater decrease (Expand Search)
Showing 1 - 20 results of 27,889 for search '(( significantly predicted increases ) OR ( significantly ((teer decrease) OR (linear decrease)) ))', query time: 2.62s Refine Results
  1. 1
    Multivariable linear regression analyses for predicting factors.

    Multivariable linear regression analyses for predicting factors. by Maurice Pradella (11678817)

    Published 2022
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  2. 2
    Cohesion characteristics and statistical significance analysis of different ingredients across IDDSI levels<sup>b'*'</sup>.

    Cohesion characteristics and statistical significance analysis of different ingredients across IDDSI levels<sup>b'*'</sup>. by Muxi Chen (9294270)

    Published 2025
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  3. 3
    Adhesion characteristics and statistical significance analysis of different ingredients across IDDSI levels<sup>b'*'</sup>.

    Adhesion characteristics and statistical significance analysis of different ingredients across IDDSI levels<sup>b'*'</sup>. by Muxi Chen (9294270)

    Published 2025
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  4. 4
    Hardness characteristics and statistical significance analysis of different ingredients across IDDSI levels<sup>b'*'</sup>.

    Hardness characteristics and statistical significance analysis of different ingredients across IDDSI levels<sup>b'*'</sup>. by Muxi Chen (9294270)

    Published 2025
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  5. 5
    Multivariate linear regression models for three approaches.

    Multivariate linear regression models for three approaches. by Bulent Gucyetmez (849602)

    Published 2024
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  6. 6
    Distribution of the same ingredient across different IDDSI levels (Percentages and frequencies) and statistical significance analysis (Chi-square analysis).

    Distribution of the same ingredient across different IDDSI levels (Percentages and frequencies) and statistical significance analysis (Chi-square analysis). by Muxi Chen (9294270)

    Published 2025
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  7. 7
    Multiple linear regression analysis results.

    Multiple linear regression analysis results. by Muxi Chen (9294270)

    Published 2025
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  8. 8
    Distribution of different ingredients at the same IDDSI level (Percentage and frequency) and statistical significance analysis (Chi-square test)<sup>b'*'</sup>.

    Distribution of different ingredients at the same IDDSI level (Percentage and frequency) and statistical significance analysis (Chi-square test)<sup>b'*'</sup>. by Muxi Chen (9294270)

    Published 2025
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  9. 9
    Moderate increases to viral infectivity are not predicted to significantly impact immunological outcomes.

    Moderate increases to viral infectivity are not predicted to significantly impact immunological outcomes. by Adrianne L. Jenner (11133854)

    Published 2021
    “…The resulting model dynamics for viral load, inflammatory macrophages, CD8<sup>+</sup> T cells, unbound IL-6 and unbound IFN were compared, and no significant changes in kinetics were predicted.</p>…”
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  10. 10
    N-acetilcysteine prevents the <i>A</i>. <i>simplex</i> CE-induced TEER decrease.

    N-acetilcysteine prevents the <i>A</i>. <i>simplex</i> CE-induced TEER decrease. by Noelia Carballeda-Sangiao (2889611)

    Published 2020
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  11. 11
    The summarized graph for the values of the coefficients of significant linear trends.

    The summarized graph for the values of the coefficients of significant linear trends. by Ekaterina Ivanova (230383)

    Published 2022
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  12. 12
    Significance (p-value), standard error, and R<sup>2</sup> scores for the linear relation between maximum dispersal distance and cross-validated AUC (AUC-cv) across all the network models for each study species.

    Significance (p-value), standard error, and R<sup>2</sup> scores for the linear relation between maximum dispersal distance and cross-validated AUC (AUC-cv) across all the network... by Damian O. Ortiz-Rodríguez (17343308)

    Published 2023
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  13. 13
    Model fit for Mixed-Effects Multi-linear Regressions with PSS as a continuous outcome measure.

    Model fit for Mixed-Effects Multi-linear Regressions with PSS as a continuous outcome measure. by Laura S. P. Bloomfield (3820531)

    Published 2024
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  14. 14
    Hardness increase across different IDDSI levels and food categories.

    Hardness increase across different IDDSI levels and food categories. by Muxi Chen (9294270)

    Published 2025
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  15. 15
    Comparison of measured and predicted values of empirical model prediction.

    Comparison of measured and predicted values of empirical model prediction. by Hongqi Wang (2208238)

    Published 2024
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  16. 16
    Model fit for Mixed-Effects Multi-linear Regressions with PSS-Moderate (PSS> = 14) as a binary outcome measure.

    Model fit for Mixed-Effects Multi-linear Regressions with PSS-Moderate (PSS> = 14) as a binary outcome measure. by Laura S. P. Bloomfield (3820531)

    Published 2024
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  17. 17
    The linearly decreasing convergence factor a.

    The linearly decreasing convergence factor a. by Junhao Wei (6816803)

    Published 2025
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  18. 18
    Brain regions with significantly decreased activations for the Raven task are shown in blue.

    Brain regions with significantly decreased activations for the Raven task are shown in blue. by Morteza Fattahi (15892028)

    Published 2025
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  19. 19
    Statistically significant linear increase in use of antidepressants during the observed time period.

    Statistically significant linear increase in use of antidepressants during the observed time period. by Jelena Filimonovic (22305307)

    Published 2025
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  20. 20
    Weighted Linear Regression Analysis of BRI and ASM/BMI.

    Weighted Linear Regression Analysis of BRI and ASM/BMI. by Wei Huang (36889)

    Published 2025
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