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Classifiers for tumour shape and internal enhancement were constructed using multiple logistic regression subject to elastic net constraints.
A predictor for the HEIP of tumour size based on the size-related CEIP was constructed using multivariate linear regression subject to elastic net constraints [28].
Another transformation then further simplifies the detection problem into the framework of a linear regression subject to additive white Gaussian noises, leading to a numerically efficient solution of the considered problem.
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This also indicates that our model relies more heavily on the non-lexical route: although outliers in the regression, subjects 1 and 2 did fit the overall model whereas subject 15 did not.
In multivariable regression, subjects with increased age at transplant (p = 0.008), diabetes (p = 0.002), and a higher baseline PWV score (p < 0.001) were at increased risk of having a high PWV score 12 months post transplant.
Classifiers for tumour margin were constructed using ordinal logistic regression, also subject to elastic net constraints.
In this setting, ordinary regression is subject to overfitting and instability of coefficients (Harrell et al., 1996), and stepwise variable selection methods do not scale well (Yuan and Lin, 2006).
In the case of the Cox proportional hazard model, this algorithm maximizes the partial likelihood of the regression coefficients subject to a constraint imposed on the sum of the absolute value of all regression coefficients in the model.
As shown by (A9), in the absence of other sources of ecologic bias, log-linear ecologic regression is subject to pure specification bias, approximated by the second term in (A9).
Briefly, the LASSO approach minimizes the residual sum of squares in a multiple regression model subject to the constraint that the sum of the absolute values of the standardized coefficients is less than a specified constant.
In the multivariable logistic regression model, subjects with RA had significantly greater odds of needing help with personal care than subjects without arthritis and those with OA (p < 0.01).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com