lmmulti: Linear regression multivariable models: 'finalfit' model...

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Linear regression multivariable models: finalfit model wrapper

Description

Using finalfit conventions, produces a multivariable linear regression model for a set of explanatory variables against a continuous dependent.

Usage

lmmulti(.data, dependent, explanatory, weights = "", ...)

Arguments

.data	Dataframe.
dependent	Character vector of length 1: name of depdendent variable (must a continuous vector).
explanatory	Character vector of any length: name(s) of explanatory variables.
weights	Character vector of length 1: name of variabe for weighting. 'Prior weights' to be used in the fitting process.
...	Other arguments to pass to lm.

Details

Uses lm with finalfit modelling conventions. Output can be passed to fit2df.

Value

A multivariable lm fitted model.

See Also

fit2df

Other finalfit model wrappers: coxphmulti(), coxphuni(), crrmulti(), crruni(), glmmixed(), glmmulti_boot(), glmmulti(), glmuni(), lmmixed(), lmuni(), svyglmmulti(), svyglmuni()

Examples

library(finalfit)
library(dplyr)

explanatory = c("age.factor", "sex.factor", "obstruct.factor", "perfor.factor")
dependent = "nodes"

colon_s %>%
  lmmulti(dependent, explanatory) %>%
  fit2df()

finalfit documentation built on Sept. 11, 2024, 9:01 p.m.