lmmulti {finalfit} | R Documentation |
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 |
Details
Uses lm
with finalfit
modelling conventions.
Output can be passed to fit2df
.
Value
A multivariable lm
fitted model.
See Also
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()
[Package finalfit version 1.0.8 Index]