Nothing
start.val.tpm <-
function (start.val, data, type, constraint) {
n <- nrow(data)
p <- ncol(data)
randStrVal <- length(start.val) == 1 && start.val == "random"
cmptStrVal <- is.null(start.val) || randStrVal || length(start.val) != 3 * p
if (cmptStrVal) {
rs <- as.vector(rowSums(data, na.rm = TRUE))
len.uni <- length(unique(rs))
rs <- factor(rs, labels = 1:len.uni)
rs <- as.numeric(levels(rs))[as.integer(rs)]
z <- cbind(1, seq(-3, 3, len = len.uni)[rs])
if (randStrVal)
z[, 2] <- rnorm(n)
old <- options(warn = (2))
on.exit(options(old))
coefs <- matrix(0, p, 2)
for (i in 1:p) {
y <- data[, i]
na.ind <- !is.na(y)
y. <- y[na.ind]
z. <- z[na.ind, ]
fm <- try(glm.fit(z., y., family = binomial()), silent = TRUE)
coefs[i, ] <- if (!inherits(fm, "try-error")) {
fm$coef
} else {
c(0, 1)
}
}
coefs <- cbind(qlogis(seq(0.05, 0.15, length = p))[order(order(coefs[, 1], decreasing = TRUE))], coefs)
coefs <- if (type == "rasch") c(coefs[, 1:2], abs(mean(coefs[, 3]))) else as.vector(coefs)
} else {
coefs <- start.val
coefs[, 1] <- qlogis(coefs[, 1])
coefs <- if (type == "rasch") c(coefs[, 1:2], abs(mean(coefs[, 3]))) else as.vector(coefs)
}
if (!is.null(constraint)) {
if (type == "rasch" && any(ind <- constraint[, 2] == 3))
coefs[-c((constraint[!ind, 2] - 1) * p + constraint[!ind, 1], length(coefs))]
else
coefs[-((constraint[, 2] - 1) * p + constraint[, 1])]
} else
coefs
}
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