Nothing
#' @export
print.cKendall <- function(x, ...) {
cat("\n Test for quasi-independence with conditional Kendall's tau\n")
cat("\n Call: ")
print(x$Call)
if (x$a != 0)
cat(paste("\nTransformation is applied with parameter a =", round(x$a, 4)))
cat(paste("\n", "Kendall's tau =", round(x$PE, 4), ", SE =", round(x$SE, 4),
", Z =", round(x$STAT, 4), ", p-value = ", round(x$p.value, 4), "\n\n"))
}
#' @export
coef.trReg <- function(object, ...) {
tmp <- object$PE[,1]
names(tmp) <- object$vNames
return(tmp)
}
#' @export
print.pmcc <- function(x, ...) {
cat("\n Test for quasi-independence with conditional correlation coefficient\n")
cat("\n Call: ")
print(x$Call)
if (x$a != 0)
cat(paste("\nTransformation is applied with parameter a =", round(x$a, 4)))
cat(paste("\n", "Correlation coefficient =", round(x$PE, 4), ", SE =", round(x$SE, 4),
", Z =", round(x$STAT, 4), ", p-value = ", round(x$p.value, 4), "\n\n"))
}
#' @export
print.trSurvfit <- function(x, ...) {
cat("\n Fitting structural transformation model \n")
cat("\n Call: ")
print(x$Call)
cat(paste("\n", "Conditional Kendall's tau =",
round(x$iniKendall, 4), ", p-value =", round(x$iniP, 4)))
cat(paste("\n", "Restricted inverse probability weighted Kendall's tau =",
round(x$iniKendall.ipw, 4), ", p-value =", round(x$iniP.ipw, 4)))
cat(paste("\n Transformation parameter by minimizing absolute value of Kendall's tau:",
round(x$byTau$par, 4)))
cat(paste("\n Transformation parameter by maximizing p-value of the test:",
round(x$byP$par, 4), "\n\n"))
}
#' @export
#' @importFrom stats model.matrix printCoefmat sd
print.trReg <- function(x, ...) {
cat("\n Call:")
print(x$Call)
cat("\n Sample size =", nrow(x$.data))
cat("\n Number of events = ", sum(x$.data$status))
x$breaks[which.min(x$breaks)] <- -Inf
x$breaks[which.max(x$breaks)] <- Inf
if (length(x$a) > 1) {
cat("\n\n The segments and the corresponding transformation parameters are:")
for (i in 1:length(x$a)) {
cat("\n In segment",
paste("(", round(x$breaks[i], 3), ", ", round(x$breaks[i + 1], 3), "]", sep = ""),
", the transformation parameter is", x$a[i])
}
cat("\n")
} else cat("\n\n Transformation parameter is", x$a, "\n")
cat("\n Standard errors obtained from", x$B, "bootstrap samples.\n")
tab <- cbind(coef = round(x$PE[,1], 3),
"se(coef)" = round(x$SE, 3),
z = round(x$PE[,1] / x$SE, 3),
"Pr(>|z|)" = round(2 * pnorm(-abs(x$PE[,1] / x$SE)), 3))
rownames(tab) <- x$varNames
printCoefmat(as.data.frame(tab), P.values = TRUE, has.Pvalue = TRUE)
cat("\n")
if (!is.null(x$PEta)) {
cat("\n Coefficient estimates for transformed truncation times used in the adjusted model:\n")
if (is.matrix(x$PEta))
tab2 <- cbind(coef = round(x$PEta[, "coef"], 3),
"se(coef)" = round(x$PEta[, "se(coef)"], 3),
z = round(x$PEta[, "z"], 3),
"Pr(>|z|)" = round(x$PEta[, "Pr(>|z|)"], 3))
## tab2 <- cbind(coef = round(x$PEta[,1], 3),
## "se(coef)" = round(x$PEta[,3], 3),
## z = round(x$PEta[,4], 3),
## "Pr(>|z|)" = round(x$PEta[,5], 3))
else tab2 <- cbind(coef = round(x$PEta[1], 3),
"se(coef)" = round(x$PEta[3], 3),
z = round(x$PEta[4], 3),
"Pr(>|z|)" = round(x$PEta[5], 3))
rownames(tab2) <- rownames(x$PEta)
printCoefmat(as.data.frame(tab2), P.values = TRUE, has.Pvalue = TRUE)
cat("\n")
}
}
#' @export
summary.trReg <- function(object, ...) {
print(object)
}
#' @export
print.trgof <- function(x, ...) {
cat("\n Overall signficances based on left-truncated regression model: p-value =", round(x$pval, 4))
if (x$input != "Surv") {
cat("\n\n The segments and the corresponding transformation parameters are:")
x$breaks[which.min(x$breaks)] <- -Inf
x$breaks[which.max(x$breaks)] <- Inf
for (i in 1:length(x$fitQs)) {
cat("\n For segment",
paste("(", round(x$breaks[i], 3), ", ", round(x$breaks[i + 1], 3), "]", sep = ""),
", the transformation parameter is", unique(x$fitQs[[i]]$a))
}
}
cat("\n\n")
}
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