View source: R/logistic_reg_adj_diff.R

logistic_reg_adj_diff | R Documentation |

This function works with `gtsummary::add_difference()`

to calculate
adjusted differences and confidence intervals based on results from a
logistic regression model. Adjustment covariates are set to the mean to
estimate the adjusted difference. The function uses bootstrap methods to
estimate the adjusted difference between two groups.
The CI is estimate by either using the SD from the bootstrap difference
estimates and calculating the CI assuming normality or using the centiles
of the bootstrapped differences as the confidence limits

The function can also be used in `add_p()`

, and if you do, be sure to
set `boot_n = 1`

to avoid long, unused computation.

logistic_reg_adj_diff( data, variable, by, adj.vars, conf.level, type, ci_type = c("sd", "centile"), boot_n = 250, ... )

`data` |
a data frame |

`variable` |
string of binary variable in |

`by` |
string of the |

`adj.vars` |
character vector of variable names to adjust model for |

`conf.level` |
Must be strictly greater than 0 and less than 1. Defaults to 0.95, which corresponds to a 95 percent confidence interval. |

`type` |
string indicating the summary type |

`ci_type` |
string dictation bootstrap method for CI estimation.
Must be one of |

`boot_n` |
number of bootstrap iterations to use. In most cases, it is
reasonable to used 250 for the |

`...` |
not used |

tibble with difference estimate

Example 1

Example 2

Other gtsummary-related functions:
`add_inline_forest_plot()`

,
`add_sparkline()`

,
`as_ggplot()`

,
`bold_italicize_group_labels()`

,
`style_tbl_compact()`

,
`tbl_likert()`

,
`theme_gtsummary_msk()`

library(gtsummary) tbl <- tbl_summary(trial, by = trt, include = response, missing = "no") # Example 1 ----------------------------------------------------------------- logistic_reg_adj_diff_ex1 <- tbl %>% add_difference( test = everything() ~ logistic_reg_adj_diff, adj.vars = "stage" ) # Example 2 ----------------------------------------------------------------- # Use the centile method, and # change the number of bootstrap resamples to perform logistic_reg_adj_diff_ex2 <- tbl %>% add_difference( test = everything() ~ purrr::partial(logistic_reg_adj_diff, ci_type = "centile", boot_n = 100), adj.vars = "stage" )

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