Nothing
# pes calculations
pes_ci <- function(Fstat,
df1,
df2,
conf.level = .95){
pes = Fstat * df1 / (Fstat*df1+df2)
F_limits <- conf.limits.ncf(F.value = Fstat,
df.1 = df1,
df.2 = df2,
conf.level = conf.level)
if(all(is.na(F_limits))){
F_limits$Lower.Limit = 0
F_limits$Upper.Limit = 0
}
LL_lambda <- F_limits$Lower.Limit
UL_lambda <- F_limits$Upper.Limit
LL_partial_eta2 <- LL_lambda / (LL_lambda + df1 + df2 + 1)
UL_partial_eta2 <- UL_lambda / (UL_lambda + df1 + df2 + 1)
if (is.na(LL_partial_eta2)) {
LL_partial_eta2 <- 0
}
if (is.na(UL_partial_eta2)) {
UL_partial_eta2 <- 1
}
cint = c(LL_partial_eta2 ,UL_partial_eta2)
return(cint)
}
conf.limits.ncf = function (F.value = NULL,
conf.level = 0.95,
df.1 = NULL, df.2 = NULL,
alpha.lower = NULL,
alpha.upper = NULL,
tol = 1e-09, Jumping.Prop = 0.1)
{
if (Jumping.Prop <= 0 | Jumping.Prop >= 1)
stop("The Jumping Proportion ('Jumping.Prop') must be between zero and one.")
if (is.null(F.value))
stop("Your 'F.value' is not correctly specified.")
if (F.value < 0)
stop("Your 'F.value' is not correctly specified.")
if (is.null(df.1) | is.null(df.2))
stop("You must specify the degrees of freedom ('df.1' and 'df.2').")
if (is.null(alpha.lower) & is.null(alpha.upper) & is.null(conf.level))
stop("You need to specify the confidence interval parameters.")
if ((!is.null(alpha.lower) | !is.null(alpha.upper)) & !is.null(conf.level))
stop("You must specify only one method of defining the confidence limits.")
if (!is.null(conf.level)) {
if (conf.level >= 1 | conf.level <= 0)
stop("Your confidence level ('conf.level') must be between 0 and 1.")
alpha.lower <- alpha.upper <- (1 - conf.level)/2
}
if (alpha.lower == 0)
alpha.lower <- NULL
if (alpha.upper == 0)
alpha.upper <- NULL
FAILED <- NULL
if (!is.null(alpha.lower)) {
LL.0 <- qf(p = alpha.lower * 5e-04, df1 = df.1, df2 = df.2)
Diff <- pf(q = F.value, df1 = df.1, df2 = df.2, ncp = LL.0) -
(1 - alpha.lower)
if (pf(q = F.value, df1 = df.1, df2 = df.2, ncp = LL.0) <
(1 - alpha.lower)) {
FAILED <- if (pf(q = F.value, df1 = df.1, df2 = df.2,
ncp = 0) < 1 - alpha.lower)
LL.0 <- 1e-08
if (pf(q = F.value, df1 = df.1, df2 = df.2, ncp = LL.0) <
1 - alpha.lower)
FAILED <- TRUE
}
if (is.null(FAILED)) {
LL.1 <- LL.2 <- LL.0
while (Diff > tol) {
LL.2 <- LL.1 * (1 + Jumping.Prop)
Diff <- pf(q = F.value, df1 = df.1, df2 = df.2,
ncp = LL.2) - (1 - alpha.lower)
LL.1 <- LL.2
}
LL.1 <- LL.2/(1 + Jumping.Prop)
LL.Bounds <- c(LL.1, (LL.1 + LL.2)/2, LL.2)
Diff <- pf(q = F.value, df1 = df.1, df2 = df.2, ncp = LL.Bounds[2]) -
(1 - alpha.lower)
while (abs(Diff) > tol) {
Diff.1 <- pf(q = F.value, df1 = df.1, df2 = df.2,
ncp = LL.Bounds[1]) - (1 - alpha.lower) > tol
Diff.2 <- pf(q = F.value, df1 = df.1, df2 = df.2,
ncp = LL.Bounds[2]) - (1 - alpha.lower) > tol
Diff.3 <- pf(q = F.value, df1 = df.1, df2 = df.2,
ncp = LL.Bounds[3]) - (1 - alpha.lower) > tol
if (Diff.1 == TRUE & Diff.2 == TRUE & Diff.3 ==
FALSE) {
LL.Bounds <- c(LL.Bounds[2], (LL.Bounds[2] +
LL.Bounds[3])/2, LL.Bounds[3])
}
if (Diff.1 == TRUE & Diff.2 == FALSE & Diff.3 ==
FALSE) {
LL.Bounds <- c(LL.Bounds[1], (LL.Bounds[1] +
LL.Bounds[2])/2, LL.Bounds[2])
}
Diff <- pf(q = F.value, df1 = df.1, df2 = df.2,
ncp = LL.Bounds[2]) - (1 - alpha.lower)
}
LL <- LL.Bounds[2]
}
}
if (!is.null(FAILED))
LL <- NA
if (!is.null(alpha.upper)) {
FAILED.Up <- NULL
UL.0 <- qf(p = 1 - alpha.upper * 5e-04, df1 = df.1, df2 = df.2)
Diff <- pf(q = F.value, df1 = df.1, df2 = df.2, ncp = UL.0) -
alpha.upper
if (Diff < 0)
UL.0 <- 1e-08
Diff <- pf(q = F.value, df1 = df.1, df2 = df.2, ncp = UL.0) -
alpha.upper
if (Diff < 0) {
FAILED.Up <- TRUE
}
if (is.null(FAILED.Up)) {
UL.1 <- UL.2 <- UL.0
while (Diff > tol) {
UL.2 <- UL.1 * (1 + Jumping.Prop)
Diff <- pf(q = F.value, df1 = df.1, df2 = df.2,
ncp = UL.2) - alpha.upper
UL.1 <- UL.2
}
UL.1 <- UL.2/(1 + Jumping.Prop)
UL.Bounds <- c(UL.1, (UL.1 + UL.2)/2, UL.2)
Diff <- pf(q = F.value, df1 = df.1, df2 = df.2, ncp = UL.Bounds[2]) -
alpha.upper
while (abs(Diff) > tol) {
Diff.1 <- pf(q = F.value, df1 = df.1, df2 = df.2,
ncp = UL.Bounds[1]) - alpha.upper > tol
Diff.2 <- pf(q = F.value, df1 = df.1, df2 = df.2,
ncp = UL.Bounds[2]) - alpha.upper > tol
Diff.3 <- pf(q = F.value, df1 = df.1, df2 = df.2,
ncp = UL.Bounds[3]) - alpha.upper > tol
if (Diff.1 == TRUE & Diff.2 == TRUE & Diff.3 ==
FALSE) {
UL.Bounds <- c(UL.Bounds[2], (UL.Bounds[2] +
UL.Bounds[3])/2, UL.Bounds[3])
}
if (Diff.1 == TRUE & Diff.2 == FALSE & Diff.3 ==
FALSE) {
UL.Bounds <- c(UL.Bounds[1], (UL.Bounds[1] +
UL.Bounds[2])/2, UL.Bounds[2])
}
Diff <- pf(q = F.value, df1 = df.1, df2 = df.2,
ncp = UL.Bounds[2]) - alpha.upper
}
UL <- UL.Bounds[2]
}
if (!is.null(FAILED.Up))
UL <- NA
}
if (!is.null(alpha.lower) & !is.null(alpha.upper))
return(list(Lower.Limit = LL, Prob.Less.Lower = 1 - pf(q = F.value,
df1 = df.1, df2 = df.2, ncp = LL), Upper.Limit = UL,
Prob.Greater.Upper = pf(q = F.value, df1 = df.1,
df2 = df.2, ncp = UL)))
if (is.null(alpha.lower) & !is.null(alpha.upper))
return(list(Upper.Limit = UL, Prob.Greater.Upper = pf(q = F.value,
df1 = df.1, df2 = df.2, ncp = UL)))
if (!is.null(alpha.lower) & is.null(alpha.upper))
return(list(Lower.Limit = LL, Prob.Less.Lower = 1 - pf(q = F.value,
df1 = df.1, df2 = df.2, ncp = LL)))
}
pes_curv = function (Fstat,
df1,
df2,
steps = 5000) {
intrvls <- (0:steps)/steps
intrvls = subset(intrvls,intrvls>0 & intrvls<1)
# Confidence interval of the SMD from Goulet-Pelletier & Cousineau
results <-
suppressWarnings({
lapply(
intrvls,
FUN = function(i)
pes_ci(
Fstat = Fstat,
df1 =
df1,
df2 =
df2,
conf.level = i
)
)
})
df <- data.frame(do.call(rbind, results))
intrvl.limit <- c("lower.limit", "upper.limit")
colnames(df) <- intrvl.limit
df$intrvl.width <- (abs((df$upper.limit) - (df$lower.limit)))
df$intrvl.level <- intrvls
df$cdf <- (abs(df$intrvl.level/2)) + 0.5
df$pvalue <- 1 - intrvls
df$svalue <- -log2(df$pvalue)
df <- head(df, -1)
class(df) <- c("data.frame", "concurve")
densdf <- data.frame(c(df$lower.limit, df$upper.limit))
colnames(densdf) <- "x"
densdf <- head(densdf, -1)
class(densdf) <- c("data.frame", "concurve")
return(list(df, densdf))
}
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