finalfit: glmmulti_boot – R documentation

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glmmulti_boot

Binomial logistic regression multivariable models with bootstrapped confidence intervals: finalfit model wrapper

Description

Using finalfit conventions, produces a multivariable binomial logistic regression models for a set of explanatory variables against a binary dependent.

Usage

glmmulti_boot(.data, dependent, explanatory, R = 1000)

Arguments

`.data`	Dataframe.
`dependent`	Character vector length 1: name of depdendent variable (must have 2 levels).
`explanatory`	Character vector of any length: name(s) of explanatory variables.
`R`	Number of draws.

Details

Uses glm with finalfit modelling conventions. boot::boot is used to draw bootstrapped confidence intervals on fixed effect model coefficients. Output can be passed to fit2df.

Value

A multivariable glm fitted model with bootstrapped confidence intervals. Output is of class glmboot.

Examples

library(finalfit)
library(dplyr)
## Note number of draws set to 100 just for speed in this example
explanatory = c("age.factor", "sex.factor", "obstruct.factor", "perfor.factor")
dependent = "mort_5yr"

colon_s %>%
  glmmulti_boot(dependent, explanatory, R=100) %>%
  fit2df(estimate_suffix="(multivariable (BS CIs))")

finalfit

Quickly Create Elegant Regression Results Tables and Plots when Modelling

v1.0.2

MIT + file LICENCE

Authors

Ewen Harrison [aut, cre], Tom Drake [aut], Riinu Ots [aut]

Initial release