proportion_ci.md
In cardx: Extra Analysis Results Data Utilities

check the proportion_ci_*() functions work

Code
  wilson_dbl <- proportion_ci_wilson(x_dbl, conf.level = 0.9, correct = FALSE)

Code
  wilsoncc_dbl <- proportion_ci_wilson(x_dbl, conf.level = 0.9, correct = TRUE)

Code
  wilson_lgl <- proportion_ci_wilson(x_lgl, conf.level = 0.9, correct = FALSE)

Code
  proportion_ci_wilson(x_rsp, conf.level = 0.9)
Output
  $N
  [1] 10

  $conf.level
  [1] 0.9

  $estimate
    p 
  0.5

  $statistic
  X-squared 
          0

  $p.value
  [1] 1

  $parameter
  df 
   1

  $conf.low
  [1] 0.2692718

  $conf.high
  [1] 0.7307282

  $method
  Wilson Confidence Interval without continuity correction

  $alternative
  [1] "two.sided"

Code
  proportion_ci_wilson(x_true)
Output
  $N
  [1] 32

  $conf.level
  [1] 0.95

  $estimate
  p 
  1

  $statistic
  X-squared 
         32

  $p.value
  [1] 1.541726e-08

  $parameter
  df 
   1

  $conf.low
  [1] 0.8928208

  $conf.high
  [1] 1

  $method
  Wilson Confidence Interval without continuity correction

  $alternative
  [1] "two.sided"

Code
  proportion_ci_wilson(x_false)
Output
  $N
  [1] 32

  $conf.level
  [1] 0.95

  $estimate
  p 
  0

  $statistic
  X-squared 
         32

  $p.value
  [1] 1.541726e-08

  $parameter
  df 
   1

  $conf.low
  [1] 0

  $conf.high
  [1] 0.1071792

  $method
  Wilson Confidence Interval without continuity correction

  $alternative
  [1] "two.sided"

Code
  wald_dbl <- proportion_ci_wald(x_dbl, conf.level = 0.9, correct = FALSE)

Code
  waldcc_dbl <- proportion_ci_wald(x_dbl, conf.level = 0.9, correct = TRUE)

Code
  wald_lgl <- proportion_ci_wald(x_lgl, conf.level = 0.9, correct = FALSE)

Code
  proportion_ci_wald(x_rsp, conf.level = 0.95, correct = TRUE)
Output
  $N
  [1] 10

  $estimate
  [1] 0.5

  $conf.low
  [1] 0.1401025

  $conf.high
  [1] 0.8598975

  $conf.level
  [1] 0.95

  $method
  Wald Confidence Interval with continuity correction

Code
  proportion_ci_wald(x_true)
Output
  $N
  [1] 32

  $estimate
  [1] 1

  $conf.low
  [1] 1

  $conf.high
  [1] 1

  $conf.level
  [1] 0.95

  $method
  Wald Confidence Interval without continuity correction

Code
  proportion_ci_wald(x_false)
Output
  $N
  [1] 32

  $estimate
  [1] 0

  $conf.low
  [1] 0

  $conf.high
  [1] 0

  $conf.level
  [1] 0.95

  $method
  Wald Confidence Interval without continuity correction

Code
  clopper_pearson_dbl <- proportion_ci_clopper_pearson(x_dbl, conf.level = 0.9)

Code
  clopper_pearson_lgl <- proportion_ci_clopper_pearson(x_lgl, conf.level = 0.9)

Code
  proportion_ci_clopper_pearson(x_rsp, conf.level = 0.95)
Output
  $N
  [1] 10

  $conf.level
  [1] 0.95

  $estimate
  probability of success 
                     0.5

  $statistic
  number of successes 
                    5

  $p.value
  [1] 1

  $parameter
  number of trials 
                10

  $conf.low
  [1] 0.187086

  $conf.high
  [1] 0.812914

  $method
  [1] "Clopper-Pearson Confidence Interval"

  $alternative
  [1] "two.sided"

Code
  proportion_ci_wilson(x_true)
Output
  $N
  [1] 32

  $conf.level
  [1] 0.95

  $estimate
  p 
  1

  $statistic
  X-squared 
         32

  $p.value
  [1] 1.541726e-08

  $parameter
  df 
   1

  $conf.low
  [1] 0.8928208

  $conf.high
  [1] 1

  $method
  Wilson Confidence Interval without continuity correction

  $alternative
  [1] "two.sided"

Code
  proportion_ci_wilson(x_false)
Output
  $N
  [1] 32

  $conf.level
  [1] 0.95

  $estimate
  p 
  0

  $statistic
  X-squared 
         32

  $p.value
  [1] 1.541726e-08

  $parameter
  df 
   1

  $conf.low
  [1] 0

  $conf.high
  [1] 0.1071792

  $method
  Wilson Confidence Interval without continuity correction

  $alternative
  [1] "two.sided"

Code
  agresti_coull_dbl <- proportion_ci_agresti_coull(x_dbl, conf.level = 0.9)

Code
  agresti_coull_lgl <- proportion_ci_agresti_coull(x_lgl, conf.level = 0.9)

Code
  proportion_ci_agresti_coull(x_rsp, conf.level = 0.95)
Output
  $N
  [1] 10

  $estimate
  [1] 0.5

  $conf.low
  [1] 0.2365931

  $conf.high
  [1] 0.7634069

  $conf.level
  [1] 0.95

  $method
  [1] "Agresti-Coull Confidence Interval"

Code
  proportion_ci_agresti_coull(x_true)
Output
  $N
  [1] 32

  $estimate
  [1] 1

  $conf.low
  [1] 0.8726819

  $conf.high
  [1] 1

  $conf.level
  [1] 0.95

  $method
  [1] "Agresti-Coull Confidence Interval"

Code
  proportion_ci_agresti_coull(x_false)
Output
  $N
  [1] 32

  $estimate
  [1] 0

  $conf.low
  [1] 0

  $conf.high
  [1] 0.1273181

  $conf.level
  [1] 0.95

  $method
  [1] "Agresti-Coull Confidence Interval"

Code
  jeffreys_dbl <- proportion_ci_jeffreys(x_dbl, conf.level = 0.9)

Code
  jeffreys_lgl <- proportion_ci_jeffreys(x_lgl, conf.level = 0.9)

Code
  proportion_ci_jeffreys(x_rsp, conf.level = 0.95)
Output
  $N
  [1] 10

  $estimate
  [1] 0.5

  $conf.low
  [1] 0.2235287

  $conf.high
  [1] 0.7764713

  $conf.level
  [1] 0.95

  $method
  Jeffreys Interval

Code
  proportion_ci_jeffreys(x_true)
Output
  $N
  [1] 32

  $estimate
  [1] 1

  $conf.low
  [1] 0.9250722

  $conf.high
  [1] 1

  $conf.level
  [1] 0.95

  $method
  Jeffreys Interval

Code
  proportion_ci_jeffreys(x_false)
Output
  $N
  [1] 32

  $estimate
  [1] 0

  $conf.low
  [1] 0

  $conf.high
  [1] 0.07492776

  $conf.level
  [1] 0.95

  $method
  Jeffreys Interval

Code
  proportion_ci_wilson(x_dbl, conf.level = c(0.9, 0.9))
Condition
  Error in `proportion_ci_wilson()`:
  ! The `conf.level` argument must be length 1.

Code
  proportion_ci_wilson(mtcars$cyl)
Condition
  Error in `proportion_ci_wilson()`:
  ! Expecting `x` to be either <logical> or <numeric/integer> coded as 0 and 1.

check the proportion_ci_strat_wilson() function works

Code
  proportion_ci_strat_wilson(x = rsp, strata = strata, weights = weights,
    correct = FALSE)
Output
  $N
  [1] 80

  $estimate
  [1] 0.625

  $conf.low
  [1] 0.4867191

  $conf.high
  [1] 0.7186381

  $conf.level
  [1] 0.95

  $method
  Stratified Wilson Confidence Interval without continuity correction

Code
  proportion_ci_strat_wilson(x = rsp, strata = strata, weights = weights,
    correct = TRUE)
Output
  $N
  [1] 80

  $estimate
  [1] 0.625

  $conf.low
  [1] 0.4482566

  $conf.high
  [1] 0.7531474

  $conf.level
  [1] 0.95

  $method
  Stratified Wilson Confidence Interval with continuity correction

Code
  proportion_ci_strat_wilson(x = as.numeric(rsp), strata = strata, weights = weights)
Output
  $N
  [1] 80

  $estimate
  [1] 0.625

  $conf.low
  [1] 0.4867191

  $conf.high
  [1] 0.7186381

  $conf.level
  [1] 0.95

  $method
  Stratified Wilson Confidence Interval without continuity correction

Code
  proportion_ci_strat_wilson(x = as.numeric(rsp), strata = strata)
Output
  $N
  [1] 80

  $estimate
  [1] 0.625

  $conf.low
  [1] 0.5242016

  $conf.high
  [1] 0.7268788

  $conf.level
  [1] 0.95

  $weights
        a.x       b.x       a.y       b.y       a.z       b.z 
  0.2111332 0.1890860 0.1180990 0.1544903 0.1737106 0.1534809

  $method
  Stratified Wilson Confidence Interval without continuity correction

Code
  proportion_ci_strat_wilson(x = rep_len(TRUE, length(rsp)), strata = strata,
  weights = weights)
Condition
  Error in `proportion_ci_strat_wilson()`:
  ! All values in `x` argument are either `TRUE` or `FALSE` and CI is not estimable.

Code
  proportion_ci_strat_wilson(x = rep_len(FALSE, length(rsp)), strata = strata,
  weights = weights)
Condition
  Error in `proportion_ci_strat_wilson()`:
  ! All values in `x` argument are either `TRUE` or `FALSE` and CI is not estimable.

Code
  proportion_ci_strat_wilson(x = as.numeric(rsp), strata = strata,
  max.iterations = -1)
Condition
  Error in `proportion_ci_strat_wilson()`:
  ! Argument `max.iterations` must be a positive integer.

Code
  proportion_ci_strat_wilson(x = as.numeric(rsp), strata = strata,
  max.iterations = -1)
Condition
  Error in `proportion_ci_strat_wilson()`:
  ! Argument `max.iterations` must be a positive integer.

Code
  proportion_ci_strat_wilson(x = as.numeric(rsp), strata = strata, weights = weights +
    pi / 5)
Condition
  Error in `proportion_ci_strat_wilson()`:
  ! The sum of the `weights` argument must be 1

Code
  proportion_ci_strat_wilson(x = as.numeric(rsp), strata = strata, weights = weights +
    pi)
Condition
  Error in `proportion_ci_strat_wilson()`:
  ! The `weights` argument must be in the interval `[0, 1]`.