fit_model: Function that fits models supported by 'mfp2'
In mfp2: Multivariable Fractional Polynomial Models with Extensions

fit_model

R Documentation

Function that fits models supported by `mfp2`

Description

Fits generalized linear models and Cox proportional hazard models.

Usage

fit_model(
  x,
  y,
  family = "gaussian",
  weights = NULL,
  offset = NULL,
  method = NULL,
  strata = NULL,
  control = NULL,
  rownames = NULL,
  nocenter = NULL,
  fast = TRUE
)

Arguments

`x`	a matrix of predictors (excluding intercept) with column names. If column names are not provided they are set according to `colnames(x, do.NULL = FALSE)`.
`y`	a vector for the outcome variable for glms, and a `Surv` object for Cox models.
`family`	a character strong specifying glm family to be used, or "cox" for Cox models. The default family is set to 'Gaussian'.
`method`	a character string specifying the method for tie handling. See `survival::coxph()`.
`strata, control, weights, offset, rownames, nocenter`	parameters for Cox or glm. See `survival::coxph()` or `stats::glm()` for details.
`fast`	passed to `fit_glm()` and `fit_cox()`. @return A list with the following components: `logl`: the log likelihood of the fitted model. `coefficients`: regression coefficients. `df`: number of parameters (degrees of freedom). `sse`: residual sum of squares. `fit`: the object returned by the fitting procedure.