add_ci.tbl_svysummary.md
In gtsummary: Presentation-Ready Data Summary and Analytic Result Tables

add_ci(method) after `add_overall()`

Code
  dplyr::select(as.data.frame(add_ci(add_overall(tbl_svysummary(svy_trial, by = trt,
    include = c(age, grade), missing = "no", statistic = list(all_continuous() ~
      "{mean}", all_categorical() ~ "{p}%")))), col_label = FALSE),
  -all_stat_cols())
Output
    label ci_stat_0 ci_stat_1 ci_stat_2
  1   Age    45, 49    44, 50    45, 50
  2 Grade      <NA>      <NA>      <NA>
  3     I  28%, 41%  27%, 46%  24%, 42%
  4    II  28%, 41%  24%, 43%  27%, 45%
  5   III  26%, 39%  23%, 42%  24%, 42%

add_ci(include)

Code
  dplyr::select(as.data.frame(add_ci(add_overall(tbl_svysummary(svy_trial,
    include = c(age, grade), by = trt, missing = "no")), include = age),
  col_label = FALSE), -all_stat_cols())
Message
  A confidence interval for the mean in variable "age" was requested; however, the primary table does not contain a mean.
Output
    label ci_stat_0 ci_stat_1 ci_stat_2
  1   Age    45, 49    44, 50    45, 50
  2 Grade      <NA>      <NA>      <NA>
  3     I      <NA>      <NA>      <NA>
  4    II      <NA>      <NA>      <NA>
  5   III      <NA>      <NA>      <NA>

add_ci(statistic)

Code
  as.data.frame(add_ci(tbl_svysummary(svy_trial, include = c(age, grade),
  missing = "no"), statistic = list(all_continuous() ~ "{conf.low} - {conf.high}",
  all_categorical() ~ "{conf.low}% - {conf.high}%")))
Message
  A confidence interval for the mean in variable "age" was requested; however, the primary table does not contain a mean.
Output
    **Characteristic** **N = 200** **95% CI**
  1                Age 47 (38, 57)    45 - 49
  2              Grade        <NA>       <NA>
  3                  I    68 (34%)  28% - 41%
  4                 II    68 (34%)  28% - 41%
  5                III    64 (32%)  26% - 39%

add_ci(pattern)

Code
  as.data.frame(add_ci(tbl_svysummary(svy_trial, include = c(age, grade),
  missing = "no", statistic = list(age = "{mean}")), include = age, pattern = "{stat} [{ci}]"))
Output
    **Characteristic** **N = 200** [**95% CI**]
  1                Age              47 [45, 49]
  2              Grade                     <NA>
  3                  I                 68 (34%)
  4                 II                 68 (34%)
  5                III                 64 (32%)

add_ci(pattern) messaging

Code
  add_ci(tbl_svysummary(svy_trial, include = age, missing = "no", statistic = list(
    age = "{mean}")), pattern = "{not_a_stat} [{ci}]")
Condition
  Error in `add_ci()`:
  ! The `pattern` argument allows only for elements "stat" and "ci" to be included in curly brackets.

Code
  add_ci(tbl_svysummary(svy_trial, include = age, missing = "no", statistic = list(
    age = "{mean}")), pattern = "{ci}")
Condition
  Error in `add_ci()`:
  ! The `pattern` argument must include references to both "{stat}" and "{ci}"

add_ci(method) messaging

Code
  add_ci(tbl_svysummary(svy_trial, include = age, missing = "no", statistic = list(
    age = "{mean}")), method = list(age = "xxxxxxxxxx"))
Condition
  Error in `add_ci()`:
  ! The value of the `method` argument for continuous variable "age" must be one of "svymean", "svymedian", "svymedian.mean", "svymedian.beta", "svymedian.xlogit", "svymedian.asin", and "svymedian.score"

Code
  add_ci(tbl_svysummary(svy_trial, include = grade), method = list(grade = "svymean"))
Condition
  Error in `add_ci()`:
  ! The value of the `method` argument for categorical variable "grade" must be one of "svyprop", "svyprop.logit", "svyprop.likelihood", "svyprop.asin", "svyprop.beta", "svyprop.mean", and "svyprop.xlogit"

add_ci() correctly handles dichotomous variables

Code
  as.data.frame(tbl)
Output
    **Characteristic** **N = 200** **95% CI**
  1     Tumor Response   132 (68%)   61%, 75%
  2              Grade    64 (32%)   26%, 39%