Selected article for: "half plasma colostral life and IgG concentration"

Author: Pipkin, K.M.; Hagey, J.V.; Rayburn, M.C.; Chigerwe, M.
Title: A Randomized Clinical Trial Evaluating Metabolism of Colostral and Plasma Derived Immunoglobulin G in Jersey Bull Calves
  • Document date: 2015_4_9
  • ID: 7nmaf6u0_12
    Snippet: To evaluate the decay of colostral or plasma derived IgG, serum half-life for the 2 groups of calves was determined by a nonlinear regression analysis using a 1-phase exponential decay model with random effects for calf initial serum IgG concentration. 12 Differences in serum IgG half-life between the 2 groups were evaluated by comparing the rate constants using an F-test. The general predicted nonlinear regression model was represented as below:.....
    Document: To evaluate the decay of colostral or plasma derived IgG, serum half-life for the 2 groups of calves was determined by a nonlinear regression analysis using a 1-phase exponential decay model with random effects for calf initial serum IgG concentration. 12 Differences in serum IgG half-life between the 2 groups were evaluated by comparing the rate constants using an F-test. The general predicted nonlinear regression model was represented as below:

    Search related documents:
    Co phrase search for related documents
    • exponential decay and regression model: 1, 2, 3, 4, 5
    • exponential decay model and rate constant: 1
    • IgG concentration and nonlinear regression: 1
    • IgG concentration and nonlinear regression model: 1
    • IgG concentration and plasma colostral: 1, 2, 3, 4, 5
    • IgG concentration and regression model: 1, 2
    • initial serum and regression model: 1
    • nonlinear regression analysis and regression model: 1, 2
    • nonlinear regression and random effect: 1
    • nonlinear regression and regression model: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18
    • nonlinear regression model and regression model: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14
    • plasma colostral and regression model: 1
    • random effect and regression model: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22
    • rate constant and regression model: 1