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finalfit
Using finalfit conventions, produces a multivariable linear regression model for a set of explanatory variables against a continuous dependent.
lmmulti(.data, dependent, explanatory, weights = "", ...)
A multivariable lm fitted model.
lm
Dataframe.
Character vector of length 1: name of depdendent variable (must a continuous vector).
Character vector of any length: name(s) of explanatory variables.
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.
Uses lm with finalfit modelling conventions. Output can be passed to fit2df.
fit2df
Other finalfit model wrappers: coxphmulti(), coxphuni(), crrmulti(), crruni(), glmmixed(), glmmulti_boot(), glmmulti(), glmuni(), lmmixed(), lmuni(), svyglmmulti(), svyglmuni()
coxphmulti()
coxphuni()
crrmulti()
crruni()
glmmixed()
glmmulti_boot()
glmmulti()
glmuni()
lmmixed()
lmuni()
svyglmmulti()
svyglmuni()
library(finalfit) library(dplyr) explanatory = c("age.factor", "sex.factor", "obstruct.factor", "perfor.factor") dependent = "nodes" colon_s %>% lmmulti(dependent, explanatory) %>% fit2df()
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