@@ -18117,7 +18117,7 @@
cardx coverage - 97.91%
| 32 |
- 23x |
+ 28x |
set_cli_abort_call()
|
@@ -18138,42 +18138,42 @@ cardx coverage - 97.91%
| 35 |
- 23x |
+ 28x |
check_not_missing(x)
|
| 36 |
- 23x |
+ 28x |
check_binary(x)
|
| 37 |
- 23x |
+ 28x |
check_range(conf.level, range = c(0, 1), include_bounds = c(FALSE, FALSE))
|
| 38 |
- 23x |
+ 28x |
check_scalar(conf.level)
|
| 39 |
- 23x |
+ 28x |
check_class(x = correct, "logical")
|
| 40 |
- 23x |
+ 28x |
check_scalar(correct)
|
@@ -18187,7 +18187,7 @@ cardx coverage - 97.91%
| 42 |
- 23x |
+ 28x |
x <- stats::na.omit(x)
|
@@ -18201,35 +18201,35 @@ cardx coverage - 97.91%
| 44 |
- 23x |
+ 28x |
n <- length(x)
|
| 45 |
- 23x |
+ 28x |
p_hat <- mean(x)
|
| 46 |
- 23x |
+ 28x |
z <- stats::qnorm((1 + conf.level) / 2)
|
| 47 |
- 23x |
+ 28x |
q_hat <- 1 - p_hat
|
| 48 |
- 23x |
+ 28x |
correction_factor <- ifelse(correct, 1 / (2 * n), 0)
|
@@ -18243,21 +18243,21 @@ cardx coverage - 97.91%
| 50 |
- 23x |
+ 28x |
err <- z * sqrt(p_hat * q_hat) / sqrt(n) + correction_factor
|
| 51 |
- 23x |
+ 28x |
l_ci <- max(0, p_hat - err)
|
| 52 |
- 23x |
+ 28x |
u_ci <- min(1, p_hat + err)
|
@@ -18271,56 +18271,56 @@ cardx coverage - 97.91%
| 54 |
- 23x |
+ 28x |
list(
|
| 55 |
- 23x |
+ 28x |
N = n,
|
| 56 |
- 23x |
+ 28x |
estimate = p_hat,
|
| 57 |
- 23x |
+ 28x |
conf.low = l_ci,
|
| 58 |
- 23x |
+ 28x |
conf.high = u_ci,
|
| 59 |
- 23x |
+ 28x |
conf.level = conf.level,
|
| 60 |
- 23x |
+ 28x |
method =
|
| 61 |
- 23x |
+ 28x |
glue::glue("Wald Confidence Interval {ifelse(correct, 'with', 'without')} continuity correction")
|
@@ -18418,7 +18418,7 @@ cardx coverage - 97.91%
| 75 |
- 14x |
+ 18x |
set_cli_abort_call()
|
@@ -18439,7 +18439,7 @@ cardx coverage - 97.91%
| 78 |
- 14x |
+ 18x |
check_pkg_installed(pkg = "broom")
|
@@ -18460,42 +18460,42 @@ cardx coverage - 97.91%
| 81 |
- 14x |
+ 18x |
check_not_missing(x)
|
| 82 |
- 14x |
+ 18x |
check_binary(x)
|
| 83 |
- 13x |
+ 17x |
check_class(x = correct, "logical")
|
| 84 |
- 13x |
+ 17x |
check_scalar(correct)
|
| 85 |
- 13x |
+ 17x |
check_range(conf.level, range = c(0, 1), include_bounds = c(FALSE, FALSE))
|
| 86 |
- 13x |
+ 17x |
check_scalar(conf.level)
|
@@ -18509,7 +18509,7 @@ cardx coverage - 97.91%
| 88 |
- 12x |
+ 16x |
x <- stats::na.omit(x)
|
@@ -18523,14 +18523,14 @@ cardx coverage - 97.91%
| 90 |
- 12x |
+ 16x |
n <- length(x)
|
| 91 |
- 12x |
+ 16x |
y <- stats::prop.test(x = sum(x), n = n, correct = correct, conf.level = conf.level)
|
@@ -18544,42 +18544,42 @@ cardx coverage - 97.91%
| 93 |
- 12x |
+ 16x |
list(N = n, conf.level = conf.level) |>
|
| 94 |
- 12x |
+ 16x |
utils::modifyList(val = broom::tidy(y) |> as.list()) |>
|
| 95 |
- 12x |
+ 16x |
utils::modifyList(
|
| 96 |
- 12x |
+ 16x |
list(
|
| 97 |
- 12x |
+ 16x |
method =
|
| 98 |
- 12x |
+ 16x |
glue::glue("Wilson Confidence Interval {ifelse(correct, 'with', 'without')} continuity correction")
|
@@ -18684,7 +18684,7 @@ cardx coverage - 97.91%
| 113 |
- 5x |
+ 7x |
set_cli_abort_call()
|
@@ -18705,7 +18705,7 @@ cardx coverage - 97.91%
| 116 |
- 5x |
+ 7x |
check_pkg_installed(pkg = "broom")
|
@@ -18726,28 +18726,28 @@ cardx coverage - 97.91%
| 119 |
- 5x |
+ 7x |
check_not_missing(x)
|
| 120 |
- 5x |
+ 7x |
check_binary(x)
|
| 121 |
- 5x |
+ 7x |
check_range(conf.level, range = c(0, 1), include_bounds = c(FALSE, FALSE))
|
| 122 |
- 5x |
+ 7x |
check_scalar(conf.level)
|
@@ -18761,14 +18761,14 @@ cardx coverage - 97.91%
| 124 |
- 5x |
+ 7x |
x <- stats::na.omit(x)
|
| 125 |
- 5x |
+ 7x |
n <- length(x)
|
@@ -18782,7 +18782,7 @@ cardx coverage - 97.91%
| 127 |
- 5x |
+ 7x |
y <- stats::binom.test(x = sum(x), n = n, conf.level = conf.level)
|
@@ -18796,21 +18796,21 @@ cardx coverage - 97.91%
| 129 |
- 5x |
+ 7x |
list(N = n, conf.level = conf.level) |>
|
| 130 |
- 5x |
+ 7x |
utils::modifyList(val = broom::tidy(y) |> as.list()) |>
|
| 131 |
- 5x |
+ 7x |
utils::modifyList(list(method = "Clopper-Pearson Confidence Interval"))
|
@@ -18901,7 +18901,7 @@ cardx coverage - 97.91%
| 144 |
- 7x |
+ 9x |
set_cli_abort_call()
|
@@ -18922,28 +18922,28 @@ cardx coverage - 97.91%
| 147 |
- 7x |
+ 9x |
check_not_missing(x)
|
| 148 |
- 7x |
+ 9x |
check_binary(x)
|
| 149 |
- 7x |
+ 9x |
check_range(conf.level, range = c(0, 1), include_bounds = c(FALSE, FALSE))
|
| 150 |
- 7x |
+ 9x |
check_scalar(conf.level)
|
@@ -18957,7 +18957,7 @@ cardx coverage - 97.91%
| 152 |
- 7x |
+ 9x |
x <- stats::na.omit(x)
|
@@ -18971,21 +18971,21 @@ cardx coverage - 97.91%
| 154 |
- 7x |
+ 9x |
n <- length(x)
|
| 155 |
- 7x |
+ 9x |
x_sum <- sum(x)
|
| 156 |
- 7x |
+ 9x |
z <- stats::qnorm((1 + conf.level) / 2)
|
@@ -19006,14 +19006,14 @@ cardx coverage - 97.91%
| 159 |
- 7x |
+ 9x |
x_sum_tilde <- x_sum + z^2 / 2
|
| 160 |
- 7x |
+ 9x |
n_tilde <- n + z^2
|
@@ -19034,35 +19034,35 @@ cardx coverage - 97.91%
| 163 |
- 7x |
+ 9x |
p_tilde <- x_sum_tilde / n_tilde
|
| 164 |
- 7x |
+ 9x |
q_tilde <- 1 - p_tilde
|
| 165 |
- 7x |
+ 9x |
err <- z * sqrt(p_tilde * q_tilde) / sqrt(n_tilde)
|
| 166 |
- 7x |
+ 9x |
l_ci <- max(0, p_tilde - err)
|
| 167 |
- 7x |
+ 9x |
u_ci <- min(1, p_tilde + err)
|
@@ -19076,49 +19076,49 @@ cardx coverage - 97.91%
| 169 |
- 7x |
+ 9x |
list(
|
| 170 |
- 7x |
+ 9x |
N = n,
|
| 171 |
- 7x |
+ 9x |
estimate = mean(x),
|
| 172 |
- 7x |
+ 9x |
conf.low = l_ci,
|
| 173 |
- 7x |
+ 9x |
conf.high = u_ci,
|
| 174 |
- 7x |
+ 9x |
conf.level = conf.level,
|
| 175 |
- 7x |
+ 9x |
method = "Agresti-Coull Confidence Interval"
|
@@ -19202,7 +19202,7 @@ cardx coverage - 97.91%
| 187 |
- 8x |
+ 10x |
set_cli_abort_call()
|
@@ -19223,35 +19223,35 @@ cardx coverage - 97.91%
| 190 |
- 8x |
+ 10x |
check_not_missing(x)
|
| 191 |
- 8x |
+ 10x |
check_binary(x)
|
| 192 |
- 8x |
+ 10x |
check_range(conf.level, range = c(0, 1), include_bounds = c(FALSE, FALSE))
|
| 193 |
- 8x |
+ 10x |
check_scalar(conf.level)
|
| 194 |
- 8x |
+ 10x |
x <- stats::na.omit(x)
|
@@ -19265,14 +19265,14 @@ cardx coverage - 97.91%
| 196 |
- 8x |
+ 10x |
n <- length(x)
|
| 197 |
- 8x |
+ 10x |
x_sum <- sum(x)
|
@@ -19286,35 +19286,35 @@ cardx coverage - 97.91%
| 199 |
- 8x |
+ 10x |
alpha <- 1 - conf.level
|
| 200 |
- 8x |
+ 10x |
l_ci <- ifelse(
|
| 201 |
- 8x |
+ 10x |
x_sum == 0,
|
| 202 |
- 8x |
+ 10x |
0,
|
| 203 |
- 8x |
+ 10x |
stats::qbeta(alpha / 2, x_sum + 0.5, n - x_sum + 0.5)
|
@@ -19335,28 +19335,28 @@ cardx coverage - 97.91%
| 206 |
- 8x |
+ 10x |
u_ci <- ifelse(
|
| 207 |
- 8x |
+ 10x |
x_sum == n,
|
| 208 |
- 8x |
+ 10x |
1,
|
| 209 |
- 8x |
+ 10x |
stats::qbeta(1 - alpha / 2, x_sum + 0.5, n - x_sum + 0.5)
|
@@ -19377,49 +19377,49 @@ cardx coverage - 97.91%
| 212 |
- 8x |
+ 10x |
list(
|
| 213 |
- 8x |
+ 10x |
N = n,
|
| 214 |
- 8x |
+ 10x |
estimate = mean(x),
|
| 215 |
- 8x |
+ 10x |
conf.low = l_ci,
|
| 216 |
- 8x |
+ 10x |
conf.high = u_ci,
|
| 217 |
- 8x |
+ 10x |
conf.level = conf.level,
|
| 218 |
- 8x |
+ 10x |
method = glue::glue("Jeffreys Interval")
|
@@ -19811,7 +19811,7 @@ cardx coverage - 97.91%
| 274 |
- 12x |
+ 16x |
set_cli_abort_call()
|
@@ -19832,56 +19832,56 @@ cardx coverage - 97.91%
| 277 |
- 12x |
+ 16x |
check_not_missing(x)
|
| 278 |
- 12x |
+ 16x |
check_not_missing(strata)
|
| 279 |
- 12x |
+ 16x |
check_binary(x)
|
| 280 |
- 12x |
+ 16x |
check_class(correct, "logical")
|
| 281 |
- 12x |
+ 16x |
check_scalar(correct)
|
| 282 |
- 12x |
+ 16x |
check_class(strata, "factor")
|
| 283 |
- 12x |
+ 16x |
check_range(conf.level, range = c(0, 1), include_bounds = c(FALSE, FALSE))
|
| 284 |
- 12x |
+ 16x |
check_scalar(conf.level)
|
@@ -19902,28 +19902,28 @@ cardx coverage - 97.91%
| 287 |
- 12x |
+ 16x |
is_na <- is.na(x) | is.na(strata)
|
| 288 |
- 12x |
+ 16x |
x <- x[!is_na]
|
| 289 |
- 12x |
+ 16x |
strata <- strata[!is_na]
|
| 290 |
- 6x |
+ 8x |
if (!inherits(x, "logical")) x <- as.logical(x)
|
@@ -19937,7 +19937,7 @@ cardx coverage - 97.91%
| 292 |
- 12x |
+ 16x |
if (all(x) || all(!x)) {
|
@@ -19965,14 +19965,14 @@ cardx coverage - 97.91%
| 296 |
- 10x |
+ 14x |
tbl <- table(factor(x, levels = c(FALSE, TRUE)), strata, useNA = "no")
|
| 297 |
- 10x |
+ 14x |
n_strata <- length(unique(strata))
|
@@ -19993,28 +19993,28 @@ cardx coverage - 97.91%
| 300 |
- 10x |
+ 14x |
do_iter <- FALSE
|
| 301 |
- 10x |
+ 14x |
if (is.null(weights)) {
|
| 302 |
- 3x |
+ 7x |
weights <- rep(1 / n_strata, n_strata) # Initialization for iterative procedure
|
| 303 |
- 3x |
+ 7x |
do_iter <- TRUE
|
@@ -20035,7 +20035,7 @@ cardx coverage - 97.91%
| 306 |
- 3x |
+ 7x |
if (!is_scalar_integerish(max.iterations) || max.iterations < 1) {
|
@@ -20063,35 +20063,35 @@ cardx coverage - 97.91%
| 310 |
- 8x |
+ 12x |
check_range(weights, range = c(0, 1), include_bounds = c(TRUE, TRUE))
|
| 311 |
- 7x |
+ 11x |
sum_weights <- sum(weights) |>
|
| 312 |
- 7x |
+ 11x |
round() |>
|
| 313 |
- 7x |
+ 11x |
as.integer()
|
| 314 |
- 7x |
+ 11x |
if (sum_weights != 1L || abs(sum_weights - sum(weights)) > sqrt(.Machine$double.eps)) {
|
@@ -20119,49 +20119,49 @@ cardx coverage - 97.91%
| 318 |
- 6x |
+ 10x |
xs <- tbl["TRUE", ]
|
| 319 |
- 6x |
+ 10x |
ns <- colSums(tbl)
|
| 320 |
- 6x |
+ 10x |
use_stratum <- (ns > 0)
|
| 321 |
- 6x |
+ 10x |
ns <- ns[use_stratum]
|
| 322 |
- 6x |
+ 10x |
xs <- xs[use_stratum]
|
| 323 |
- 6x |
+ 10x |
ests <- xs / ns
|
| 324 |
- 6x |
+ 10x |
vars <- ests * (1 - ests) / ns
|
@@ -20175,7 +20175,7 @@ cardx coverage - 97.91%
| 326 |
- 6x |
+ 10x |
strata_qnorm <- .strata_normal_quantile(vars, weights, conf.level)
|
@@ -20196,14 +20196,14 @@ cardx coverage - 97.91%
| 329 |
- 6x |
+ 10x |
weights_new <- if (do_iter) {
|
| 330 |
- 1x |
+ 5x |
.update_weights_strat_wilson(vars, strata_qnorm, weights, ns, max.iterations, conf.level)$weights
|
@@ -20238,7 +20238,7 @@ cardx coverage - 97.91%
| 335 |
- 6x |
+ 10x |
strata_conf.level <- 2 * stats::pnorm(strata_qnorm) - 1
|
@@ -20252,14 +20252,14 @@ cardx coverage - 97.91%
| 337 |
- 6x |
+ 10x |
ci_by_strata <- Map(
|
| 338 |
- 6x |
+ 10x |
function(x, n) {
|
@@ -20273,7 +20273,7 @@ cardx coverage - 97.91%
| 340 |
- 36x |
+ 48x |
suppressWarnings(stats::prop.test(x, n, correct = correct, conf.level = strata_conf.level)$conf.int)
|
@@ -20287,14 +20287,14 @@ cardx coverage - 97.91%
| 342 |
- 6x |
+ 10x |
x = xs,
|
| 343 |
- 6x |
+ 10x |
n = ns
|
@@ -20308,14 +20308,14 @@ cardx coverage - 97.91%
| 345 |
- 6x |
+ 10x |
lower_by_strata <- sapply(ci_by_strata, "[", 1L)
|
| 346 |
- 6x |
+ 10x |
upper_by_strata <- sapply(ci_by_strata, "[", 2L)
|
@@ -20329,14 +20329,14 @@ cardx coverage - 97.91%
| 348 |
- 6x |
+ 10x |
lower <- sum(weights_new * lower_by_strata)
|
| 349 |
- 6x |
+ 10x |
upper <- sum(weights_new * upper_by_strata)
|
@@ -20357,63 +20357,63 @@ cardx coverage - 97.91%
| 352 |
- 6x |
+ 10x |
list(
|
| 353 |
- 6x |
+ 10x |
N = length(x),
|
| 354 |
- 6x |
+ 10x |
estimate = mean(x),
|
| 355 |
- 6x |
+ 10x |
conf.low = lower,
|
| 356 |
- 6x |
+ 10x |
conf.high = upper,
|
| 357 |
- 6x |
+ 10x |
conf.level = conf.level,
|
| 358 |
- 6x |
+ 10x |
weights = if (do_iter) weights_new else NULL,
|
| 359 |
- 6x |
+ 10x |
method =
|
| 360 |
- 6x |
+ 10x |
glue::glue("Stratified Wilson Confidence Interval {ifelse(correct, 'with', 'without')} continuity correction")
|
@@ -20427,7 +20427,7 @@ cardx coverage - 97.91%
| 362 |
- 6x |
+ 10x |
compact()
|
@@ -20476,7 +20476,7 @@ cardx coverage - 97.91%
| 369 |
- 526x |
+ 536x |
is.logical(x) || (is_integerish(x) && is_empty(setdiff(x, c(0, 1, NA))))
|
@@ -20686,7 +20686,7 @@ cardx coverage - 97.91%
| 399 |
- 8x |
+ 20x |
summands <- weights^2 * vars
|
@@ -20700,7 +20700,7 @@ cardx coverage - 97.91%
| 401 |
- 8x |
+ 20x |
sqrt(sum(summands)) / sum(sqrt(summands)) * stats::qnorm((1 + conf.level) / 2)
|
@@ -20959,14 +20959,14 @@ cardx coverage - 97.91%
| 438 |
- 1x |
+ 5x |
it <- 0
|
| 439 |
- 1x |
+ 5x |
diff_v <- NULL
|
@@ -20980,70 +20980,70 @@ cardx coverage - 97.91%
| 441 |
- 1x |
+ 5x |
while (it < max.iterations) {
|
| 442 |
- 2x |
+ 10x |
it <- it + 1
|
| 443 |
- 2x |
+ 10x |
weights_new_t <- (1 + strata_qnorm^2 / n_per_strata)^2
|
| 444 |
- 2x |
+ 10x |
weights_new_b <- (vars + strata_qnorm^2 / (4 * n_per_strata^2))
|
| 445 |
- 2x |
+ 10x |
weights_new <- weights_new_t / weights_new_b
|
| 446 |
- 2x |
+ 10x |
weights_new <- weights_new / sum(weights_new)
|
| 447 |
- 2x |
+ 10x |
strata_qnorm <- .strata_normal_quantile(vars, weights_new, conf.level)
|
| 448 |
- 2x |
+ 10x |
diff_v <- c(diff_v, sum(abs(weights_new - initial_weights)))
|
| 449 |
- 1x |
+ 5x |
if (diff_v[length(diff_v)] < tol) break
|
| 450 |
- 1x |
+ 5x |
initial_weights <- weights_new
|
@@ -21064,7 +21064,7 @@ cardx coverage - 97.91%
| 453 |
- 1x |
+ 5x |
if (it == max.iterations) {
|
@@ -21092,28 +21092,28 @@ cardx coverage - 97.91%
| 457 |
- 1x |
+ 5x |
list(
|
| 458 |
- 1x |
+ 5x |
"n_it" = it,
|
| 459 |
- 1x |
+ 5x |
"weights" = weights_new,
|
| 460 |
- 1x |
+ 5x |
"diff_v" = diff_v
|
@@ -39245,14 +39245,14 @@ cardx coverage - 97.91%
| 41 |
- 25x |
+ 35x |
check_not_missing(data)
|
| 42 |
- 25x |
+ 35x |
UseMethod("ard_categorical_ci")
|
@@ -39392,14 +39392,14 @@ cardx coverage - 97.91%
| 62 |
- 12x |
+ 22x |
set_cli_abort_call()
|
| 63 |
- 12x |
+ 22x |
check_dots_empty()
|
@@ -39420,7 +39420,7 @@ cardx coverage - 97.91%
| 66 |
- 12x |
+ 22x |
check_pkg_installed(pkg = "broom")
|
@@ -39441,35 +39441,35 @@ cardx coverage - 97.91%
| 69 |
- 12x |
+ 22x |
cards::process_selectors(data, variables = {{ variables }}, by = {{ by }})
|
| 70 |
- 12x |
+ 22x |
method <- arg_match(method)
|
| 71 |
- 12x |
+ 22x |
if (method %in% c("strat_wilson", "strat_wilsoncc")) {
|
| 72 |
- 2x |
+ 4x |
cards::process_selectors(data, strata = strata)
|
| 73 |
- 2x |
+ 4x |
check_scalar(strata)
|
@@ -39483,21 +39483,21 @@ cardx coverage - 97.91%
| 75 |
- 12x |
+ 22x |
cards::process_formula_selectors(
|
| 76 |
- 12x |
+ 22x |
data[variables],
|
| 77 |
- 12x |
+ 22x |
value = value
|
@@ -39511,7 +39511,7 @@ cardx coverage - 97.91%
| 79 |
- 12x |
+ 22x |
check_not_missing(variables)
|
@@ -39532,7 +39532,7 @@ cardx coverage - 97.91%
| 82 |
- 12x |
+ 22x |
if (is_empty(variables)) {
|
@@ -39567,28 +39567,28 @@ cardx coverage - 97.91%
| 87 |
- 12x |
+ 22x |
map(
|
| 88 |
- 12x |
+ 22x |
variables,
|
| 89 |
- 12x |
+ 22x |
function(variable) {
|
| 90 |
- 20x |
+ 30x |
levels <- .unique_values_sort(data, variable = variable, value = value[[variable]])
|
@@ -39602,63 +39602,63 @@ cardx coverage - 97.91%
| 92 |
- 20x |
+ 30x |
.calculate_ard_proportion(
|
| 93 |
- 20x |
+ 30x |
data = .as_dummy(data, variable = variable, levels = levels, by = by, strata = strata),
|
| 94 |
- 20x |
+ 30x |
variables = c(everything(), -all_of(c(by, strata))),
|
| 95 |
- 20x |
+ 30x |
by = all_of(by),
|
| 96 |
- 20x |
+ 30x |
method = method,
|
| 97 |
- 20x |
+ 30x |
conf.level = conf.level,
|
| 98 |
- 20x |
+ 30x |
strata = strata,
|
| 99 |
- 20x |
+ 30x |
weights = weights,
|
| 100 |
- 20x |
+ 30x |
max.iterations = max.iterations
|
@@ -39679,35 +39679,35 @@ cardx coverage - 97.91%
| 103 |
- 20x |
+ 30x |
dplyr::left_join(
|
| 104 |
- 20x |
+ 30x |
dplyr::select(., "variable") |>
|
| 105 |
- 20x |
+ 30x |
dplyr::distinct() |>
|
| 106 |
- 20x |
+ 30x |
dplyr::mutate(variable_level = as.list(.env$levels)),
|
| 107 |
- 20x |
+ 30x |
by = "variable"
|
@@ -39728,14 +39728,14 @@ cardx coverage - 97.91%
| 110 |
- 20x |
+ 30x |
dplyr::mutate(variable = .env$variable) |>
|
| 111 |
- 20x |
+ 30x |
dplyr::relocate("variable_level", .after = "variable")
|
@@ -39756,7 +39756,7 @@ cardx coverage - 97.91%
| 114 |
- 12x |
+ 22x |
dplyr::bind_rows()
|
@@ -39784,140 +39784,140 @@ cardx coverage - 97.91%
| 118 |
- 20x |
+ 30x |
cards::ard_complex(
|
| 119 |
- 20x |
+ 30x |
data = data,
|
| 120 |
- 20x |
+ 30x |
variables = {{ variables }},
|
| 121 |
- 20x |
+ 30x |
by = {{ by }},
|
| 122 |
- 20x |
+ 30x |
statistic =
|
| 123 |
- 20x |
+ 30x |
~ list(
|
| 124 |
- 20x |
+ 30x |
prop_ci =
|
| 125 |
- 20x |
+ 30x |
switch(method,
|
| 126 |
- 20x |
+ 30x |
"waldcc" = \(x, ...) proportion_ci_wald(x, conf.level = conf.level, correct = TRUE),
|
| 127 |
- 20x |
+ 30x |
"wald" = \(x, ...) proportion_ci_wald(x, conf.level = conf.level, correct = FALSE),
|
| 128 |
- 20x |
+ 30x |
"wilsoncc" = \(x, ...) proportion_ci_wilson(x, conf.level = conf.level, correct = TRUE),
|
| 129 |
- 20x |
+ 30x |
"wilson" = \(x, ...) proportion_ci_wilson(x, conf.level = conf.level, correct = FALSE),
|
| 130 |
- 20x |
+ 30x |
"clopper-pearson" = \(x, ...) proportion_ci_clopper_pearson(x, conf.level = conf.level),
|
| 131 |
- 20x |
+ 30x |
"agresti-coull" = \(x, ...) proportion_ci_agresti_coull(x, conf.level = conf.level),
|
| 132 |
- 20x |
+ 30x |
"jeffreys" = \(x, ...) proportion_ci_jeffreys(x, conf.level = conf.level),
|
| 133 |
- 20x |
+ 30x |
"strat_wilsoncc" = \(x, data, ...) {
|
| 134 |
- 1x |
+ 2x |
proportion_ci_strat_wilson(x,
|
| 135 |
- 1x |
+ 2x |
strata = data[[strata]], weights = weights,
|
| 136 |
- 1x |
+ 2x |
max.iterations = max.iterations,
|
| 137 |
- 1x |
+ 2x |
conf.level = conf.level, correct = TRUE
|
@@ -39938,35 +39938,35 @@ cardx coverage - 97.91%
| 140 |
- 20x |
+ 30x |
"strat_wilson" = \(x, data, ...) {
|
| 141 |
- 1x |
+ 2x |
proportion_ci_strat_wilson(x,
|
| 142 |
- 1x |
+ 2x |
strata = data[[strata]], weights = weights,
|
| 143 |
- 1x |
+ 2x |
max.iterations = max.iterations,
|
| 144 |
- 1x |
+ 2x |
conf.level = conf.level, correct = FALSE
|
@@ -40008,14 +40008,14 @@ cardx coverage - 97.91%
| 150 |
- 20x |
+ 30x |
dplyr::mutate(
|
| 151 |
- 20x |
+ 30x |
context = "proportion_ci"
|
@@ -40050,7 +40050,7 @@ cardx coverage - 97.91%
| 156 |
- 250x |
+ 260x |
unique_levels <-
|
@@ -40064,21 +40064,21 @@ cardx coverage - 97.91%
| 158 |
- 250x |
+ 260x |
if (is.logical(data[[variable]])) c(TRUE, FALSE)
|
| 159 |
- 250x |
+ 260x |
else if (is.factor(data[[variable]])) factor(levels(data[[variable]]), levels = levels(data[[variable]]))
|
| 160 |
- 250x |
+ 260x |
else unique(data[[variable]]) |> sort()
|
@@ -40099,7 +40099,7 @@ cardx coverage - 97.91%
| 163 |
- 250x |
+ 260x |
if (!is_empty(value) && !value %in% unique_levels) {
|
@@ -40162,14 +40162,14 @@ cardx coverage - 97.91%
| 172 |
- 250x |
+ 260x |
if (!is_empty(value)) {
|
| 173 |
- 19x |
+ 29x |
unique_levels <- value
|
@@ -40190,7 +40190,7 @@ cardx coverage - 97.91%
| 176 |
- 250x |
+ 260x |
unique_levels
|
@@ -40225,28 +40225,28 @@ cardx coverage - 97.91%
| 181 |
- 20x |
+ 30x |
map(levels, ~ data[[variable]] == .x) |>
|
| 182 |
- 20x |
+ 30x |
set_names(paste0("this_is_not_a_column_name_anyone_would_choose_", variable, "_", levels, "...")) %>%
|
| 183 |
- 20x |
+ 30x |
{dplyr::tibble(!!!.)} |> # styler: off
|
| 184 |
- 20x |
+ 30x |
dplyr::bind_cols(data[c(by, strata)])
|