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Correlations of log hsTnT were first examined by single variable linear or logistic regression and presented as nonadjusted coefficient (NAC) and 95% confidence interval (95% CI).
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Age was also fitted as a continuous variable (linear trend).
We ran multiple variable linear regression models with robust standard errors (α = 0.05).
Multiple variable linear regressions will be undertaken to determine statistically independent predictors of the threshold of delay time.
To assist interpretation, effects of continuous variables (linear, quadratic, or cubic terms) have not been tabulated but instead recategorised into strata in the results (certain results will not make sense unless this is borne in mind).
Accelerated life test (ALT) planning in Bayesian framework is studied in this paper with a focus of differentiating competing acceleration models, when there is uncertainty as to whether the relationship between log mean life and the stress variable is linear or exhibits some curvature.
The subnetwork was linked to the outcome variable through linear or nonlinear relationship.
The method is applicable to Gaussian or non-Gaussian variables with linear or non-linear failure boundaries.
The method is powerful as it makes no assumptions about the nature of the relationship between the variables, whether linear or any other.
In mathematics and automatic control, an equation system is discussed as discrete or continuous one with the type of input variables and linear or nonlinear one according to the relationship between the input and output.
Model gam1 shows whether the trend of the variables was linear or not.
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