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

add_ci(include)

Code
  as.data.frame(add_ci(add_overall(tbl_summary(trial, include = c(age, grade),
  by = trt, missing = "no")), include = age))
Message
  A confidence interval for the mean in variable "age" was requested; however, the primary table does not contain a mean.
Output
    **Characteristic** **Overall**  \nN = 200 **95% CI** **Drug A**  \nN = 98
  1                Age            47 (38, 57)     45, 49          46 (37, 60)
  2              Grade                   <NA>       <NA>                 <NA>
  3                  I               68 (34%)       <NA>             35 (36%)
  4                 II               68 (34%)       <NA>             32 (33%)
  5                III               64 (32%)       <NA>             31 (32%)
    **95% CI** **Drug B**  \nN = 102 **95% CI**
  1     44, 50           48 (39, 56)     45, 50
  2       <NA>                  <NA>       <NA>
  3       <NA>              33 (32%)       <NA>
  4       <NA>              36 (35%)       <NA>
  5       <NA>              33 (32%)       <NA>

add_ci(statistic)

Code
  as.data.frame(add_ci(tbl_summary(trial, include = c(age, grade), by = trt,
  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** **Drug A**  \nN = 98 **95% CI** **Drug B**  \nN = 102
  1                Age          46 (37, 60)    44 - 50           48 (39, 56)
  2              Grade                 <NA>       <NA>                  <NA>
  3                  I             35 (36%)  26% - 46%              33 (32%)
  4                 II             32 (33%)  24% - 43%              36 (35%)
  5                III             31 (32%)  23% - 42%              33 (32%)
    **95% CI**
  1    45 - 50
  2       <NA>
  3  24% - 42%
  4  26% - 45%
  5  24% - 42%

add_ci(pattern)

Code
  as.data.frame(add_ci(tbl_summary(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_summary(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_summary(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_summary(trial, include = age, missing = "no", statistic = list(age = "{mean}")),
  method = list(age = "wilson"))
Condition
  Error in `add_ci()`:
  ! The value of the `method` argument for continuous variable "age" must be one of "t.test" and "wilcox.test"

Code
  add_ci(tbl_summary(trial, include = grade), method = list(grade = "t.test"))
Condition
  Error in `add_ci()`:
  ! The value of the `method` argument for categorical variable "grade" must be one of "wald", "wald.no.correct", "exact", "wilson", "wilson.no.correct", "agresti.coull", and "jeffreys"

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%