mirror of
https://github.com/agdamsbo/stRoke.git
synced 2024-11-25 06:01:54 +01:00
246 lines
6.8 KiB
R
246 lines
6.8 KiB
R
|
|
|
|
#' @title Calculates the probability of winning
|
|
#' @description Calculates the probability of winning (winP). In the referenced
|
|
#' article Zou et al (2022) proposes a method for calculating probability of
|
|
#' winning with a confidence interval an p-value testing.
|
|
#' @param data A data frame containing the response and group variable.
|
|
#' @param response The name of the response variable.
|
|
#' Takes first column if empty.
|
|
#' @param group The name of the group variable.
|
|
#' Takes second column if empty.
|
|
#' @param alpha The alpha level for the hypothesis test. Default is 0.05.
|
|
#' @param beta The beta level for the sample size calculation. Default is 0.2.
|
|
#' @param group.ratio The ratio of group sizes. Default is 1.
|
|
#' @param sample.size Flag to include sample size calculation. Default is FALSE.
|
|
#' @param print.tables Flag to print cumulative tables. Default is FALSE.
|
|
#' @param dec Numeric for decimals to print. Default is 3.
|
|
#' @return A list containing the win_prob statistics.
|
|
#' @export
|
|
#' @importFrom stats pnorm qnorm xtabs
|
|
#' @source \doi{10.1161/STROKEAHA.121.037744}
|
|
#' @examples
|
|
#' win_prob(data=stRoke::talos,response="mrs_6",group="rtreat")
|
|
win_prob <-
|
|
function(data,
|
|
response = NULL,
|
|
group = NULL,
|
|
alpha = 0.05,
|
|
beta = 0.2,
|
|
group.ratio = 1,
|
|
sample.size = FALSE,
|
|
print.tables = FALSE,
|
|
dec = 3) {
|
|
if (is.null(response)) {
|
|
response <- names(data)[1]
|
|
}
|
|
|
|
if (is.null(group)) {
|
|
group <- names(data)[2]
|
|
}
|
|
|
|
group_levels <- levels(factor(data[, group]))
|
|
|
|
if (length(group_levels) != 2) {
|
|
stop("The group has to contain 2, and only 2 levels.")
|
|
}
|
|
|
|
if (!is.numeric(group.ratio)) {
|
|
stop("Group ratio must be a numeric")
|
|
}
|
|
|
|
if (!is.logical(sample.size)) {
|
|
stop("Sample size must be a logical")
|
|
}
|
|
|
|
# Internal helper function for calculating ranks
|
|
freq_rank <- function(data, x = "Freq") {
|
|
lapply(data, function(i) {
|
|
rank <- c()
|
|
n_i <- nrow(i)
|
|
for (j in seq_len(n_i)) {
|
|
if (j < n_i) {
|
|
rank[j] <-
|
|
((i[j, x] + 1) / 2 + (sum(i[seq_len(n_i)[(j + 1):n_i], x])))
|
|
}
|
|
if (j == n_i) {
|
|
rank[j] <- (i[j, x] + 1) / 2
|
|
}
|
|
}
|
|
cbind(i, rank)
|
|
})
|
|
}
|
|
|
|
overall <-
|
|
freq_rank(list(data.frame(xtabs(data = data[c(response)]))))[[1]]
|
|
|
|
tbl <- xtabs(data = data[c(response, group)])
|
|
|
|
tbl_df <- data.frame(tbl)
|
|
|
|
prop_df <- data.frame(proportions(tbl, group))
|
|
|
|
df <- cbind(tbl_df, prop = prop_df[, "Freq"])
|
|
|
|
list_cum <- split(df, df[, group])
|
|
|
|
list_cum <- lapply(list_cum, function(i) {
|
|
data.frame(i, overall_rank = overall$rank)
|
|
})
|
|
|
|
list_cum <- freq_rank(list_cum)
|
|
|
|
sum_a <- sum(df$Freq[df$rtreat == group_levels[1]])
|
|
sum_b <- sum(df$Freq[df$rtreat == group_levels[2]])
|
|
|
|
list_cum[[1]]$win_frac <-
|
|
with(list_cum[[1]], overall_rank - rank) / sum_b
|
|
list_cum[[2]]$win_frac <-
|
|
with(list_cum[[2]], overall_rank - rank) / sum_a
|
|
|
|
winP_a <- sum(with(list_cum[[1]], prop * win_frac))
|
|
winP_b <- sum(with(list_cum[[2]], prop * win_frac))
|
|
|
|
var_win_frac_a <-
|
|
sum(with(list_cum[[1]], prop * win_frac ^ 2)) - winP_a ^ 2
|
|
var_win_frac_b <-
|
|
sum(with(list_cum[[2]], prop * win_frac ^ 2)) - winP_b ^ 2
|
|
|
|
var_win_prob <- var_win_frac_a / sum_a + var_win_frac_b / sum_b
|
|
|
|
se_win_prob <- sqrt(var_win_prob)
|
|
|
|
ci_up <-
|
|
exp(log(winP_a / (1 - winP_a)) - qnorm(1 - alpha / 2) * se_win_prob /
|
|
(winP_a / (1 - winP_a))) /
|
|
(1 + exp(log(winP_a / (1 - winP_a)) - qnorm(1 - alpha / 2) *
|
|
se_win_prob / (winP_a / (1 - winP_a))))
|
|
|
|
ci_lo <-
|
|
exp(log(winP_b / (1 - winP_b)) + qnorm(1 - alpha / 2) * se_win_prob /
|
|
(winP_b / (1 - winP_b))) /
|
|
(1 + exp(log(winP_b / (1 - winP_b)) + qnorm(1 - alpha / 2) *
|
|
se_win_prob / (winP_b / (1 - winP_b))))
|
|
|
|
test_stat <-
|
|
abs(log(winP_a / (1 - winP_a))) / (se_win_prob / (winP_a * (1 - winP_a)))
|
|
p_val <- 2 * (1 - pnorm(test_stat))
|
|
|
|
nnt <- 1 / (winP_a - 0.5)
|
|
|
|
ss_n <- NA
|
|
|
|
if (sample.size) {
|
|
ss_n <-
|
|
ceiling((group.ratio + 1) / group.ratio *
|
|
(qnorm(1 - alpha / 2) + qnorm(1 - beta)) ^ 2 *
|
|
(var_win_frac_a + group.ratio * var_win_frac_b) /
|
|
(winP_a * (1 - winP_a) * log(winP_a / (1 - winP_a))) ^ 2
|
|
)
|
|
}
|
|
|
|
out <- list(
|
|
list_cum = list_cum,
|
|
group_levels = group_levels,
|
|
sum_a = sum_a,
|
|
sum_b = sum_b,
|
|
winP_a = winP_a,
|
|
winP_b = winP_b,
|
|
var_win_frac_a = var_win_frac_a,
|
|
var_win_frac_b = var_win_frac_b,
|
|
var_win_prob = var_win_prob,
|
|
se_win_prob = se_win_prob,
|
|
conf.int = c(ci_lo, ci_up),
|
|
test_stat = test_stat,
|
|
p_val = p_val,
|
|
nnt = nnt,
|
|
ss_n = ss_n,
|
|
param.record = list(
|
|
data = data,
|
|
response = response,
|
|
group = group,
|
|
alpha = alpha,
|
|
beta = beta,
|
|
group.ratio = group.ratio,
|
|
sample.size = sample.size,
|
|
print.tables = print.tables,
|
|
dec = dec
|
|
)
|
|
)
|
|
class(out) <- c("win_Prop", class(out))
|
|
return(out)
|
|
}
|
|
|
|
|
|
print.win_Prop <- function (x, ...) {
|
|
args <- list(...)
|
|
|
|
cat("\t Zou et al's winP (doi: 10.1161/STROKEAHA.121.037744) \n\n")
|
|
cat(
|
|
sprintf(
|
|
"Probability of a random observation in %s group
|
|
will have a higher response score than a random
|
|
observation in %s group:\n\n",
|
|
x$group_levels[2],
|
|
x$group_levels[1]
|
|
)
|
|
)
|
|
|
|
cat(" ")
|
|
|
|
cat(
|
|
sprintf(
|
|
"\t winP: %2.3f (%2.3f, %2.3f) p=%1.4f",
|
|
x$winP_a,
|
|
x$conf.int[1],
|
|
x$conf.int[2],
|
|
x$p_val
|
|
)
|
|
)
|
|
|
|
cat("\n")
|
|
|
|
cat("--------------------------------------------\n\n")
|
|
|
|
cat(sprintf("The numbers needed to treat (NNT) are: %s\n\n",
|
|
ceiling(x$nnt)))
|
|
|
|
cat("\n")
|
|
|
|
if (x$param.record$sample.size) {
|
|
cat("--------------------------------------------\n\n")
|
|
|
|
cat(
|
|
sprintf(
|
|
"\tWith %s/%s ratio = %s and beta = %s
|
|
the sample size needed is: %s\n\n",
|
|
x$group_levels[1],
|
|
x$group_levels[2],
|
|
x$param.record$group.ratio,
|
|
x$param.record$beta,
|
|
x$ss_n
|
|
)
|
|
)
|
|
}
|
|
|
|
cat("\n")
|
|
|
|
if (x$param.record$print.tables) {
|
|
cat("--------------------------------------------\n\n")
|
|
|
|
lc <- lapply(x$list_cum, function(i, t = c("prop", "win_frac")) {
|
|
i[t] <- round(i[t], x$param.record$dec)
|
|
i[, !names(i) == x$param.record$group]
|
|
})
|
|
|
|
for (i in x$group_levels) {
|
|
tab <- knitr::kable(lc[[i]], row.names = FALSE)
|
|
cat(sprintf("Results for the %s group:\n", i))
|
|
cat(sprintf("\t%s\n",
|
|
tab))
|
|
cat("\n")
|
|
}
|
|
}
|
|
return(invisible(x))
|
|
}
|