Add CI Column

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

# S3 method for class 'tbl_svysummary'
add_ci(
  x,
  method = list(all_continuous() ~ "svymean", all_categorical() ~ "svyprop.logit"),
  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,
  df = survey::degf(x$inputs$data),
  ...
)

Arguments

x

(tbl_summary)
a summary table of class 'tblsummary'

method

(formula-list-selector)
Confidence interval method. Default is list(all_continuous() ~ "svymean", all_categorical() ~ "svyprop.logit"). 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.

df

(numeric)
denominator degrees of freedom, passed to survey::svyciprop(df) or confint(df). Default is survey::degf(x$inputs$data).

...

These dots are for future extensions and must be empty.

Value

gtsummary table

method argument

Must be one of

• "svyprop.logit", "svyprop.likelihood", "svyprop.asin", "svyprop.beta", "svyprop.mean", "svyprop.xlogit" calculated via survey::svyciprop() for categorical variables

• "svymean" calculated via survey::svymean() for continuous variables

• "svymedian.mean", "svymedian.beta", "svymedian.xlogit", "svymedian.asin", "svymedian.score" calculated via survey::svyquantile(quantiles = 0.5) for continuous variables

Examples

data(api, package = "survey")
survey::svydesign(id = ~dnum, weights = ~pw, data = apiclus1, fpc = ~fpc) |>
  tbl_svysummary(
    by = "both",
    include = c(api00, stype),
    statistic = all_continuous() ~ "{mean} ({sd})"
  ) |>
  add_stat_label() |>
  add_ci(pattern = "{stat} (95% CI {ci})") |>
  modify_header(all_stat_cols() ~ "**{level}**") |>
  modify_spanning_header(all_stat_cols() ~ "**Survived**")


  
Characteristic
      

        
Survived
      
    
No
      
Yes
    
api00, Mean (SD)
633 (96) (95% CI 570, 696)
648 (109) (95% CI 600, 697)
stype, n (%)



    E
1,083 (64%) (95% CI 43%, 81%)
3,791 (84%) (95% CI 73%, 91%)
    H
237 (14%) (95% CI 6.6%, 27%)
237 (5.3%) (95% CI 2.1%, 13%)
    M
372 (22%) (95% CI 8.7%, 46%)
474 (11%) (95% CI 5.7%, 19%)
Abbreviation: CI = Confidence Interval