mfp.object: Multiple Fractional Polynomial Model Object

mfp.objectR Documentation

Multiple Fractional Polynomial Model Object

Description

Objects returned by fitting fractional polynomial model objects.

These are objects representing fitted mfp models. Class mfp inherits from either glm or coxph depending on the type of model fitted.

Value

In addition to the standard glm/coxph components the following components are included in a mfp object.

x

the final FP transformations that are contained in the design matrix x. The predictor "z" with 4 df would have corresponding columns "z.1" and "z.2" in x.

powers

a matrix containing the best FP powers for each predictor. If a predictor has less than two powers a NA will fill the appropriate cell of the matrix.

pvalues

a matrix containing the P-values from the closed tests. Briefly p.null is the P-value for the test of inclusion (see mfp), p.lin corresponds to the test of nonlinearity and p.FP the test of simplification. The best m=1 power (power2) and best m=2 powers (power4.1 and power4.2) are also given.

scale

all predictors are shifted and rescaled before being power transformed if nonpositive values are encountered or the range of the predictor is reasonably large. If x' would be used instead of x where x' = (x+a)/b the parameters a (shift) and b (scale) are contained in the matrix scale.

df.initial

a vector containing the degrees of freedom allocated to each predictor.

df.final

a vector containing the degrees of freedom of each predictor at convergence of the backfitting algorithm.

dev

the deviance of the final model.

dev.lin

the deviance of the model that has every predictor included with 1 df (i.e. linear).

dev.null

the deviance of the null model.

fptable

the table of the final fp transformations.

formula

the proposed formula for a call of glm/coxph.

fit

the fitted glm/coxph model using the proposed formula. This component can be used for prediction, etc.

See Also

mfp, glm.object


mfp documentation built on May 29, 2024, 9 a.m.