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mfp (version 1.4.6)

mfp.object: 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.

Arguments

Value

  • In addition to the standard glm/coxph components the following components are included in a mfp object.
  • xthe 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.
  • powersa 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.
  • pvaluesa 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.
  • scaleall 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.initiala vector containing the degrees of freedom allocated to each predictor.
  • df.finala vector containing the degrees of freedom of each predictor at convergence of the backfitting algorithm.
  • devthe deviance of the final model.
  • dev.linthe deviance of the model that has every predictor included with 1 df (i.e. linear).
  • dev.nullthe deviance of the null model.
  • fptablethe table of the final fp transformations.
  • formulathe proposed formula for a call of glm/coxph.
  • fitthe fitted glm/coxph model using the proposed formula. This component can be used for prediction, etc.

See Also

mfp, glm.object