Add CI Column

Add a new column with the confidence intervals for proportions, means, etc.

Usage

add_ci(x, ...)

# S3 method for class 'tbl_summary'
add_ci(
  x,
  method = list(all_continuous() ~ "t.test", all_categorical() ~ "wilson"),
  include = everything(),
  statistic = list(all_continuous() ~ "{conf.low}, {conf.high}", all_categorical() ~
    "{conf.low}%, {conf.high}%"),
  conf.level = 0.95,
  style_fun = list(all_continuous() ~ label_style_sigfig(), all_categorical() ~
    label_style_sigfig(scale = 100)),
  pattern = NULL,
  ...
)

Arguments

x

(tbl_summary)
a summary table of class 'tblsummary'

...

These dots are for future extensions and must be empty.

method

(formula-list-selector)
Confidence interval method. Default is list(all_continuous() ~ "t.test", all_categorical() ~ "wilson"). See details below.

include

(tidy-select)
Variables to include in the summary table. Default is everything().

statistic

(formula-list-selector)
Indicates how the confidence interval will be displayed. Default is list(all_continuous() ~ "{conf.low}, {conf.high}", all_categorical() ~ "{conf.low}%, {conf.high}%")

conf.level

(scalar real)
Confidence level. Default is 0.95

style_fun

(function)
Function to style upper and lower bound of confidence interval. Default is list(all_continuous() ~ label_style_sigfig(), all_categorical() ~ label_style_sigfig(scale = 100)).

pattern

(string)
Indicates the pattern to use to merge the CI with the statistics cell. The default is NULL, where no columns are merged. The two columns that will be merged are the statistics column, represented by "{stat}" and the CI column represented by "{ci}", e.g. pattern = "{stat} ({ci})" will merge the two columns with the CI in parentheses. Default is NULL, and no merging is performed.

Value

gtsummary table

method argument

Must be one of

• "wilson", "wilson.no.correct" calculated via prop.test(correct = c(TRUE, FALSE)) for categorical variables

• "exact" calculated via stats::binom.test() for categorical variables

• "wald", "wald.no.correct" calculated via cardx::proportion_ci_wald(correct = c(TRUE, FALSE) for categorical variables

• "agresti.coull" calculated via cardx::proportion_ci_agresti_coull() for categorical variables

• "jeffreys" calculated via cardx::proportion_ci_jeffreys() for categorical variables

• "t.test" calculated via stats::t.test() for continuous variables

• "wilcox.test" calculated via stats::wilcox.test() for continuous variables

Examples

# Example 1 ----------------------------------
trial |>
  tbl_summary(
    missing = "no",
    statistic = all_continuous() ~ "{mean} ({sd})",
    include = c(marker, response, trt)
  ) |>
  add_ci()


  
Characteristic
      
N = 2001
      
95% CI2
    
Marker Level (ng/mL)
0.92 (0.86)
0.79, 1.0
Tumor Response
61 (32%)
25%, 39%
Chemotherapy Treatment



    Drug A
98 (49%)
42%, 56%
    Drug B
102 (51%)
44%, 58%
1 Mean (SD); n (%)
    
2 CI = Confidence Interval
    

# Example 2 ----------------------------------
trial |>
  select(response, grade) %>%
  tbl_summary(
    statistic = all_categorical() ~ "{p}%",
    missing = "no",
    include = c(response, grade)
  ) |>
  add_ci(pattern = "{stat} ({ci})") |>
  modify_footnote(everything() ~ NA)


  
Characteristic
      
N = 200 (95% CI)1
    
Tumor Response
32% (25%, 39%)
Grade

    I
34% (28%, 41%)
    II
34% (28%, 41%)
    III
32% (26%, 39%)
1 CI = Confidence Interval