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meta-rate.r
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Break = "<><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><>\n"
notice = "\"meta_rate\", An R program for interrater reliability in L2 Meta-Analyses.
Copyright (C) 2019-present Reza Norouzian, [email protected]\n"
message(Break, notice, Break)
Break = "\n*********************************************************************************\n"
cite <- "To cite this package use:\n\nNorouzian,R.(2021). Interrater reliability in second language meta-analyses:\nThe case of categorical moderators. Studies in Second Language Acquisition, 43,896-915."
cat(Break, cite, Break)
#=============================================================================================================================
trim <- function(X){
X <- setNames(X, trimws(names(X)))
y <- sapply(names(X), function(x) is.character(as.vector(X[[x]])))
X[y] <- lapply(X[y], trimws)
return(X)
}
#===============================================================================================================================
d.prepos <- function(d = NA, study.name = NA, group.name = NA, n = NA, mdif = NA, stder = NA, mpre = NA, mpos = NA, sdpre = NA, sdpos = NA, r = NA, rev.sign = FALSE, rev.group = FALSE, autoreg = FALSE, t.pair = NA, df = NA, sdif = NA, post = NA, control = NA, outcome = NA, time = NA, ...)
{
}
#========================================================================================
rm.allrowNA <- function(X) {
if(inherits(X, "list")){
lapply(X, function(i) i[rowSums(is.na(i) | i == "") != ncol(i), , drop = FALSE])
} else { X[rowSums(is.na(X) | X == "") != ncol(X), , drop = FALSE] }
}
#===============================================================================================================================
rm.allcolNA <- function(X) {
if(inherits(X, "list")){
lapply(X, function(i) i[, colSums(is.na(i) | i == "") != nrow(i), drop = FALSE])
} else { X[, colSums(is.na(X) | X == "") != nrow(X), drop = FALSE] }
}
#===============================================================================================================================
rm.colrowNA <- function(X){
r <- rm.allrowNA(X)
rm.allcolNA(r)
}
#================================================================================================================================
drop.col <- function(dat, vec){
vec <- trimws(vec)
names(dat) <- trimws(names(dat))
f <- function(dat, vec) {
i1 <- !names(dat) %in% vec
setNames(dat[i1], names(dat)[i1])
}
if(inherits(dat, "list")) { lapply(dat, f, vec = vec)
} else { f(dat, vec) }
}
#================================================================================================================================
full.clean <- function(X, omit, all = TRUE, omit.auto.suffix = TRUE)
{
X <- rm.colrowNA(X)
X <- if(inherits(X, "list") & omit.auto.suffix){ lapply(X, function(x) trim(setNames(x, sub("\\.\\d+$", "", names(x)))))
} else if(inherits(X, "data.frame") & omit.auto.suffix) { trim(setNames(X, sub("\\.\\d+$", "", names(X)))) } else { X }
if(all){ X } else {
drop.col(X, vec = omit)
}
}
#===============================================================================================================================
detail2 <- function(X, useNA = "ifany"){
nr <- nrow(X)
nc <- ncol(X)
tab <- table(row(X), unlist(X), useNA = useNA)
pj <- colSums(tab)/(nr * nc)
pjk <- (colSums(tab^2) - nr * nc * pj)/(nr * nc * (nc - 1) * pj)
K <- (pjk - pj)/(1 - pj)
h <- names(K)
h[is.na(h)] <- "NA"
setNames(K, h)
}
#===============================================================================================================================
detail <- function(X, useNA = "ifany") {
X <- as.matrix(X)
tab <- table(row(X), unlist(X), useNA = useNA)
w <- diag(ncol(tab))
rosum <- rowSums(tab)
obs_oc <- tab * (t(w %*% t(tab)) - 1)
obs_c <- colSums(obs_oc)
max_oc <- tab * (rosum - 1)
max_c <- colSums(max_oc)
SA <- obs_c / max_c
h <- names(SA)
h[is.na(h)] <- "NA"
setNames(SA, h)
}
#===============================================================================================================================
set.margin <- function()
{
par(mgp = c(1.5, 0.14, 0), mar = c(2.5, 2.6, 1.8, .5),
tck = -0.02)
}
#===============================================================================================================================
splot <- function(y, main, lwd = 5, lend = 2, show.sa = FALSE, digits = 3, cex.sa = .9){
ll <- length(y)
x <- seq_len(ll)
plot(x, y, type = "h", main = main, xlim = c(.95, 1.02*max(x)), ylim = 0:1,
ylab = "SA%", xaxt = "n", xlab = "Category", lend = lend, lwd = lwd,
col = colorRampPalette(c(4, 2))(ll), font.lab = 2,
panel.first = abline(h = 0, col = 8), las = 1, cex.axis = .9)
if(show.sa) text(x[y != 0]-.015, .4, round(y[y != 0], digits), pos = 2, xpd = NA, srt = 90, font = 2, cex = cex.sa)
axis(1, at = x, labels = names(y))
}
#===============================================================================================================================
irr <- int <- function (X, nsim = 1e3, useNA = "ifany", level = .95, digits = 6, raw = TRUE)
{
if(!inherits(X, c("data.frame", "matrix", "table"))) stop("Ratings must be 'data.frame', 'matrix', and if not raw, a 'table'.", call. = FALSE)
if(raw) X <- table(row(X), unlist(X), useNA = useNA)
X2 <- X * (X - 1)
sumcol <- colSums(X)
sumrow <- rowSums(X)
nc <- ncol(X)
nr <- nrow(X)
tot <- sum(X)
pij <- X2/(sumrow * (sumrow - 1))
pi <- rowSums(pij)
p <- mean(pi)
pj <- sumcol/tot
pj2 <- pj^2
pe <- sum(pj2)
KAPPA <- (p - pe)/(1 - pe)
s <- (nc * p - 1)/(nc - 1)
pi.v.boot <- replicate(nsim, pi.boot <- sample(pi, size = nr, replace = TRUE))
p.boot <- colMeans(pi.v.boot)
s.boot <- sapply(seq_len(nsim), function(i) (nc * p.boot[i] - 1)/(nc - 1))
p <- (1 - level) / 2
s.boot.ci <- quantile(s.boot, probs = c(p, 1-p), na.rm = TRUE)
return(round(c(Fleiss_KAPPA = KAPPA,
Sindex = s,
lower = s.boot.ci[[1]],
upper = s.boot.ci[[2]],
conf.level = level), digits))
}
#===============================================================================================================================
int2 <- function(X, level = .95, useNA = "ifany", nsim = 1e3, digits = 4, raw = TRUE){
X <- table(row(X), unlist(X), useNA = useNA)
agree.mat <- as.matrix(X)
n <- nrow(agree.mat) # number of studies or groups within studies
q <- ncol(agree.mat) # number of categories
f <- 0 # population correction
weights.mat <- diag(q)
agree.mat.w <- t(weights.mat%*%t(agree.mat))
ri.vec <- agree.mat%*%rep(1,q)
sum.q <- (agree.mat*(agree.mat.w-1))%*%rep(1,q)
n2more <- sum(ri.vec>=2)
pa <- sum(sum.q[ri.vec>=2]/((ri.vec*(ri.vec-1))[ri.vec>=2]))/n2more
pi.vec <- t(t(rep(1/n,n))%*%(agree.mat/(ri.vec%*%t(rep(1,q)))))
pe <- sum(weights.mat) * sum(pi.vec*(1-pi.vec)) / (q*(q-1))
ac1 <- (pa-pe)/(1-pe)
den.ivec <- ri.vec*(ri.vec-1)
den.ivec <- den.ivec - (den.ivec == 0) # this replaces each 0 value with -1 to make the next ratio calculation always possible.
pa.ivec <- sum.q/den.ivec
pe.r2 <- pe*(ri.vec>=2)
ac1.ivec <- (n/n2more)*(pa.ivec-pe.r2)/(1-pe)
pe.ivec <- (sum(weights.mat)/(q*(q-1))) * (agree.mat%*%(1-pi.vec))/ri.vec
ac1.ivec.x <- ac1.ivec - 2*(1-ac1) * (pe.ivec-pe)/(1-pe)
var.ac1 <- ((1-f)/(n*(n-1))) * sum((ac1.ivec.x - ac1)^2)
stderr <- sqrt(var.ac1)
p.value <- 2*(1-pt(ac1/stderr,n-1))
lower <- ac1 - stderr*qt(1-(1-level)/2,n-1)
upper <- min(1,ac1 + stderr*qt(1-(1-level)/2,n-1))
return(round(c(AC = ac1, lower = lower, upper = upper, conf.level = level), digits))
}
#===============================================================================================================================
is.constant <- function(x) length(unique(x)) == 1L
#===============================================================================================================================
drop.inner.list <- function(L, what, omit.auto.suffix = TRUE) {
if(omit.auto.suffix) L <- lapply(L, function(x) setNames(x, sub("\\.\\d+$", "", names(x))))
L[!names(L) %in% what]
}
#===============================================================================================================================
meta_rate <- function(..., sub.name = "group.name", nsim = 1e3, level = .95,
useNA = "ifany", type = c("s", "ac"), na.rm = FALSE,
digits = 3, common = FALSE, all = TRUE, drop = NULL,
plot = TRUE, lwd = 5, lend = 1, show.sa = TRUE,
sub.level = NULL, study.level = NULL, file.name = NULL,
reset = TRUE, rev.page = FALSE, cex.sa = .9)
{
r <- list(...)
type <- trimws(type)
type <- match.arg(type)
if(!all(sapply(r, inherits, c("data.frame", "matrix")))) stop("Coding sheet(s) must be 'Excel CSV' files, 'data.frame' or 'matrix'.", call. = FALSE)
n.df <- length(r)
r <- lapply(r, as.data.frame)
ar <- formalArgs(d.prepos)[-c(2, 22)]
r <- full.clean(r, ar, all)
check <- all(sapply(r, function(i) "study.name" %in% names(i)))
if(!check) stop("Add a new column named 'study.name' to the coding sheet(s).", call. = FALSE)
r <- lapply(r, function(x) do.call(rbind, c(split(x, x$study.name), make.row.names = FALSE)))
drop <- trimws(drop)
drop <- drop[!drop %in% "study.name"]
if(length(drop) != 0) r <- drop.col(r, drop)
r <- unname(r)
sub.name <- trimws(sub.name)
if(n.df == 1) tbl <- table(names(r[[1]])[!names(r[[1]]) %in% c("study.name", sub.name)])
com.names <- if(n.df >= 2) {
ok <- is.constant(sapply(r, nrow))
if(!ok) stop("The coding sheets don't have the same number of rows.", call. = FALSE)
vec <- names(unlist(r, recursive = FALSE))
unique(vec[duplicated(vec)])
} else {
names(which(tbl >= 2))
}
dot.names <- if(all) com.names else com.names[!com.names %in% ar]
if(length(dot.names) == 0) stop("No 2 raters detected OR no two moderators names match.", call. = FALSE)
if(n.df >= 2) {
r <- do.call(cbind, r)
tbl <- table(names(r)[!names(r) %in% c("study.name", sub.name)])
} else { r <- r[[1]]
}
n.coder <- tbl[tbl >= 2]
i1 <- colnames(r) != 'study.name'
st.level <- names(which(sapply(split.default(r[i1], names(r)[i1]), function(x)
base::all(!colSums(!aggregate(.~ study.name, transform(x, study.name = r$study.name), FUN = is.constant)[-1])))))
st.level <- st.level[st.level %in% dot.names]
exclude <- trimws(sub.level)
st.level <- st.level[!st.level %in% c(exclude,"study.name", sub.name)]
L <- split.default(r[names(r) %in% dot.names], names(r)[names(r) %in% dot.names])
if(length(st.level) != 0) L[st.level] <- lapply(L[st.level], function(x) x[ave(seq_along(x[[1]]), r$study.name, FUN = seq_along) == 1, ])
L <- drop.inner.list(L, c("study.name", sub.name))
if(na.rm) L <- lapply(L, na.omit)
f <- if(type == "s") int else int2
out <- lapply(L, f, nsim = nsim, level = level, digits = digits, useNA = useNA, raw = TRUE)
A <- lapply(L, detail, useNA = useNA)
study.level <- sapply(seq_along(out), function(i) names(out)[[i]] %in% st.level)
d <- data.frame(out)
d[] <- lapply(d, as.list)
if(plot){
n <- length(L)
if(reset){
graphics.off()
org.par <- par(no.readonly = TRUE)
on.exit(par(org.par))
}
dev <- if(!rev.page) n2mfrow(n) else rev(n2mfrow(n))
if(n > 1L) { par(mfrow = dev) ; set.margin() }
invisible(mapply(splot, y = A, main = names(A), lwd = lwd, lend = lend, show.sa = show.sa, digits = digits, cex.sa = cex.sa))
}
res <- data.frame(t(rbind(d, row.comprd = sapply(L, nrow), min.cat = sapply(A, function(i) if(any(i < 1)) names(i)[which.min(i)] else "--"),
n.coder = n.coder, study.level = ifelse(study.level, "Yes", "No"))))
output <- data.frame(lapply(res, unlist))
if(common) output <- output[output$n.coder == max(output$n.coder),]
file.name <- trimws(file.name)
if(length(file.name) != 0){
nm <- paste0(file.name, ".csv")
ur <- try(write.csv(output, nm), silent = TRUE)
if(inherits(ur, "try-error")) stop(paste0("\nClose the Excel file '", nm, "' and try again OR pick another file name."), call. = FALSE)
message(paste0("\nNote: Check folder '", basename(getwd()),"' for the Excel file '", nm, "'.\n"))
}
return(output)
}
#================================================================================================================================================================
irr.diag <- function(X, useNA = "ifany"){
a <- detail2(X, useNA = useNA)
b <- detail(X, useNA = useNA)
round(data.frame(Fleiss_KAPPA_cat. = a, SA = b), 3)
}
#==========================================================================================================================================
find.irr <- function(X, what, sub.name = "group.name"){
if(!inherits(X, "data.frame")) stop("Data must be an Excel CSV file or a 'data.frame'.", call. = FALSE)
X <- full.clean(X)
s <- as.list(substitute(what))
res <- Filter(NROW, X[rowSums(X[grep(as.character(s[[2]]), names(X))] == s[[3]], na.rm = TRUE) > 0,][c("study.name", sub.name)])
if(length(res) == 0) NULL else res
}
#===========================# Datasets # =====================================================================================
#table1 <- read.csv("https://raw.githubusercontent.com/hkil/m/master/t1.csv", row.names = 1)
#table2 <- read.csv("https://raw.githubusercontent.com/hkil/m/master/t2.csv", row.names = 1)
#table3 <- read.csv("https://raw.githubusercontent.com/hkil/m/master/t3.csv", row.names = 1)
#table5 <- read.csv('https://raw.githubusercontent.com/hkil/m/master/t5.csv', row.names = 1)
#c1 <- read.csv("https://raw.githubusercontent.com/hkil/m/master/c1.csv")
#c2 <- read.csv("https://raw.githubusercontent.com/hkil/m/master/c2.csv")
#c3 <- read.csv("https://raw.githubusercontent.com/hkil/m/master/c3.csv")
#c4 <- read.csv("https://raw.githubusercontent.com/hkil/m/master/c4.csv")