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mixed cox regression model  (RStudio)

 
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    RStudio mixed cox regression model
    Kaplan-Meier survival curves for each batch (Clyde River, Patonga Creek, Shoalhaven River) of oysters challenged with OsHV-1 (solid line) and 95% confidence intervals (dashed line). Each batch comprised n = 73–86 oysters at the onset of the viral challenge and n = 12 live oysters were sampled from each batch on days 1, 2, 3, 5, and 7. Different letters (a and b) indicate significance (p < 0.05) identified by a <t>mixed</t> <t>Cox</t> <t>regression</t> <t>model.</t>
    Mixed Cox Regression Model, supplied by RStudio, 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/mixed+cox+regression+model/mixed+cox+regression+model/pmc06656993-182-8-22
    Average 90 stars, based on 1 article reviews
    mixed cox regression model - by Bioz Stars, 2026-09
    90/100 stars

    Images

    1) Product Images from "Influence of environment on the pathogenesis of Ostreid herpesvirus-1 (OsHV-1) infections in Pacific oysters ( Crassostrea gigas ) through differential microbiome responses"

    Article Title: Influence of environment on the pathogenesis of Ostreid herpesvirus-1 (OsHV-1) infections in Pacific oysters ( Crassostrea gigas ) through differential microbiome responses

    Journal: Heliyon

    doi: 10.1016/j.heliyon.2019.e02101

    Kaplan-Meier survival curves for each batch (Clyde River, Patonga Creek, Shoalhaven River) of oysters challenged with OsHV-1 (solid line) and 95% confidence intervals (dashed line). Each batch comprised n = 73–86 oysters at the onset of the viral challenge and n = 12 live oysters were sampled from each batch on days 1, 2, 3, 5, and 7. Different letters (a and b) indicate significance (p < 0.05) identified by a mixed Cox regression model.
    Figure Legend Snippet: Kaplan-Meier survival curves for each batch (Clyde River, Patonga Creek, Shoalhaven River) of oysters challenged with OsHV-1 (solid line) and 95% confidence intervals (dashed line). Each batch comprised n = 73–86 oysters at the onset of the viral challenge and n = 12 live oysters were sampled from each batch on days 1, 2, 3, 5, and 7. Different letters (a and b) indicate significance (p < 0.05) identified by a mixed Cox regression model.

    Techniques Used:

    Related Articles

    other:

    Article Title: Influence of environment on the pathogenesis of Ostreid herpesvirus-1 (OsHV-1) infections in Pacific oysters ( Crassostrea gigas ) through differential microbiome responses
    Article Snippet: Each batch of oysters was compared using a mixed Cox regression model , taking into account the random effect of tank, using RStudio ver.



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    Image Search Results


    Kaplan-Meier survival curves for each batch (Clyde River, Patonga Creek, Shoalhaven River) of oysters challenged with OsHV-1 (solid line) and 95% confidence intervals (dashed line). Each batch comprised n = 73–86 oysters at the onset of the viral challenge and n = 12 live oysters were sampled from each batch on days 1, 2, 3, 5, and 7. Different letters (a and b) indicate significance (p < 0.05) identified by a mixed Cox regression model.

    Journal: Heliyon

    Article Title: Influence of environment on the pathogenesis of Ostreid herpesvirus-1 (OsHV-1) infections in Pacific oysters ( Crassostrea gigas ) through differential microbiome responses

    doi: 10.1016/j.heliyon.2019.e02101

    Figure Lengend Snippet: Kaplan-Meier survival curves for each batch (Clyde River, Patonga Creek, Shoalhaven River) of oysters challenged with OsHV-1 (solid line) and 95% confidence intervals (dashed line). Each batch comprised n = 73–86 oysters at the onset of the viral challenge and n = 12 live oysters were sampled from each batch on days 1, 2, 3, 5, and 7. Different letters (a and b) indicate significance (p < 0.05) identified by a mixed Cox regression model.

    Article Snippet: Each batch of oysters was compared using a mixed Cox regression model , taking into account the random effect of tank, using RStudio ver.

    Techniques: