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qmb.summary <- function(qmboots) {
# Basic info from the analysis
nfactors <- qmboots$orig.res$brief$nfactors
nstat <- qmboots$orig.res$brief$nstat
nqsorts <- qmboots$orig.res$brief$nqsorts
#-------------------------------------------------------
# Gather results of Q-sorts
obj.loa <- as.array(paste0("qmboots$loa.stats$factor", 1:nfactors))
loa.std <- qmboots$orig.res$loa
loa.bts <- apply(obj.loa, 1,
function(x) eval(parse(text=paste0(x, "[,c('mean','sd')]"))))
loa.frq <- apply(obj.loa, 1,
function(x) eval(parse(text=paste0(x, "[,c('flag_freq')]"))))
# Give appropriate column names
dimnames(loa.frq) <- list(rownames(loa.bts[[1]]), paste0("flag.freq", 1:nfactors))
colnames(loa.std) <- paste0("f", 1:nfactors, ".std")
for (i in 1:nfactors) {
colnames(loa.bts[[i]]) <- paste0("f", i, c(".loa", ".SE"))
}
# Reorder rows in standard results (bootstrap reorders Q-sorts alphab.)
loa.std <- loa.std[rownames(loa.frq),]
# Calculate estimate of bias
loa.bts.est <- apply(obj.loa, 1,
function(x) eval(parse(text=paste0(x, "[,'mean']"))))
loa.bias <- loa.std - loa.bts.est
names(loa.bias) <- paste0("f", 1:nfactors, ".bias")
# Bind together
qs <- data.frame(loa.std, do.call("cbind", loa.bts), loa.frq, loa.bias)
#-------------------------------------------------------
# Gather results of statements
obj.zsc <- as.array(paste0("qmboots$'zscore-stats'$factor", 1:nfactors))
zsc.std <- qmboots$orig.res$zsc
zsc.bts <- apply(obj.zsc, 1,
function(x) eval(parse(text=paste0(x, "[,c('mean','sd')]"))))
# Appropriate column names
colnames(zsc.std) <- paste0("f", 1:nfactors, ".zsc.std")
for (i in 1:nfactors) {
colnames(zsc.bts[[i]]) <- paste0("f", i, c(".zsc.bts", ".SE"))
}
# And factor scores
zscn.std <- qmboots$orig.res$zsc_n
zscn.bts <- qmboots$'zscore-stats'$'Bootstraped factor scores'
colnames(zscn.bts) <- paste0("fsc.bts.", 1:nfactors)
# Calculate estimate of bias for z-scores
zsc.bts.est <- apply(obj.zsc, 1,
function(x) eval(parse(text=paste0(x, "[,'mean']"))))
zsc.bias <- zsc.std - zsc.bts.est
names(zsc.bias) <- paste0("f", 1:nfactors, ".bias")
# Calculate estimate of bias for factor scores
zscn.bias <- zscn.std - zscn.bts
names(zscn.bias) <- paste0("f", 1:nfactors, ".fsc.bias")
# Bind together
st <- data.frame(zsc.std, do.call("cbind", zsc.bts), zsc.bias,
zscn.std, zscn.bts, zscn.bias)
qmb <- list(qs, st)
names(qmb) <- c("qsorts", "statements")
return(qmb)
}
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