fit_null_step: Function to fit null model excluding variable of interest

In mfp2: Multivariable Fractional Polynomial Models with Extensions

Function to fit null model excluding variable of interest

Description

"Null" model here refers to a model which does not include the variable of interest xi. For parameter definitions, see find_best_fp_step(). All parameters captured by ... are passed on to fit_model().

Usage

fit_null_step(x, xi, y, powers_current, powers, acdx, ...)

Arguments

x	an input matrix of dimensions nobs x nvars. Does not contain intercept, but columns are already expanded into dummy variables as necessary. Data are assumed to be shifted and scaled.
xi	a character string indicating the name of the current variable of interest, for which the best fractional polynomial transformation is to be estimated in the current step.
y	a vector for the response variable or a Surv object.
powers_current	a list of length equal to the number of variables, indicating the fp powers to be used in the current step for all variables (except xi).
powers	a named list of numeric values that sets the permitted FP powers for each covariate.
acdx	a logical vector of length nvars indicating continuous variables to undergo the approximate cumulative distribution (ACD) transformation.
...	passed to fit_model().

Value

A list with two entries:

• powers: fp power(s) of xi in fitted model - in this case NA.

• metrics: a matrix with performance indices for fitted model.

mfp2 documentation built on Nov. 15, 2023, 1:06 a.m.