Report statistics from regression summary tables inline

Source: R/inline_text.tbl_regression.R

Takes an object with class tbl_regression, and the location of the statistic to report and returns statistics for reporting inline in an R markdown document. Detailed examples in the inline_text vignette

# S3 method for class 'tbl_regression'
inline_text(
  x,
  variable,
  level = NULL,
  pattern = "{estimate} ({conf.level*100}% CI {conf.low}, {conf.high}; {p.value})",
  estimate_fun = x$inputs$estimate_fun,
  pvalue_fun = label_style_pvalue(prepend_p = TRUE),
  ...
)

Arguments

x

(tbl_regression)
Object created by tbl_regression()

variable

(tidy-select)
A single variable name of statistic to present

level

(string)
Level of the variable to display for categorical variables. Default is NULL

pattern

(string)
String indicating the statistics to return. Uses glue::glue() formatting. Default is "{estimate} ({conf.level }\% CI {conf.low}, {conf.high}; {p.value})". All columns from x$table_body are available to print as well as the confidence level (conf.level). See below for details.

estimate_fun

(function)
Function to style model coefficient estimates. Columns 'estimate', 'conf.low', and 'conf.high' are formatted. Default is x$inputs$estimate_fun

pvalue_fun

function to style p-values and/or q-values. Default is label_style_pvalue(prepend_p = TRUE)

...

These dots are for future extensions and must be empty.

Value

A string reporting results from a gtsummary table

pattern argument

The following items (and more) are available to print. Use print(x$table_body) to print the table the estimates are extracted from.

  • {estimate} coefficient estimate formatted with 'estimate_fun'

  • {conf.low} lower limit of confidence interval formatted with 'estimate_fun'

  • {conf.high} upper limit of confidence interval formatted with 'estimate_fun'

  • {p.value} p-value formatted with 'pvalue_fun'

  • {N} number of observations in model

  • {label} variable/variable level label

Author

Daniel D. Sjoberg

Examples

inline_text_ex1 <-
  glm(response ~ age + grade, trial, family = binomial(link = "logit")) %>%
  tbl_regression(exponentiate = TRUE)

inline_text(inline_text_ex1, variable = age)
#> [1] "1.02 (95% CI 1.00, 1.04; p=0.10)"
inline_text(inline_text_ex1, variable = grade, level = "III")
#> [1] "1.01 (95% CI 0.47, 2.16; p>0.9)"