#' @export
print.puniformoutput <- function(x, ...) {
cat("\n")
cat("Method:", x$method)
cat("\n")
cat("\n")
cat("Effect size estimation p-uniform")
cat("\n")
cat("\n")
if (x$method == "LNP" | x$method == "LN1MINP" | x$method == "P" | x$method == "ML") {
x$pval.0 <- ifelse(x$pval.0 < 0.001, " <.001", round(x$pval.0,
4))
print(format(data.frame(est = round(x$est, 4), ci.lb = round(x$ci.lb, 4),
ci.ub = round(x$ci.ub, 4), L.0 = round(x$L.0, 4),
pval = x$pval.0, ksig = x$ksig, row.names = ""), width = 9))
cat("\n")
}
if (x$method == "KS" | x$method == "AD") {
print(format(data.frame(est = round(x$est, 4), ci.lb = round(x$ci.lb, 4),
ci.ub = round(x$ci.ub, 4), L.0 = NA, pval = NA, ksig = x$ksig,
row.names = ""), width = 9))
cat("\n")
cat("Notes:")
cat("\n")
cat("- Confidence interval does not exist for method", x$method)
cat("\n")
cat("- Test of an effect does not exist for method", x$method)
if (x$approx.est == 1) {
cat("\n")
cat("- Approximation used for estimating effect size")
}
cat("\n")
cat("\n")
} else if (x$approx.est == 1 & x$approx.ci.lb == 1 & is.na(x$est) & is.na(x$ci.lb)) {
cat("Notes:")
cat("\n")
cat("- Approximation used for estimating effect size and ci.lb, est and ci.lb <",
x$ext.lb)
if (x$method == "P") {
cat("\n")
cat("- p-value approximated with normal distribution")
}
cat("\n")
cat("\n")
} else if (x$approx.ci.lb == 1 & is.na(x$ci.lb)) {
cat("Notes:")
cat("\n")
cat("- Approximation used for estimating ci.lb, ci.lb <", x$ext.lb)
if (x$method == "P") {
cat("\n")
cat("- p-value approximated with normal distribution")
}
cat("\n")
cat("\n")
} else if (x$approx.est == 1 & x$approx.ci.lb == 1 & is.na(x$est) == FALSE & is.na(x$ci.lb) == FALSE) {
cat("Notes:")
cat("\n")
cat("- Approximation used for estimating effect size and ci.lb")
if (x$method == "P") {
cat("\n")
cat("- p-value approximated with normal distribution")
}
cat("\n")
cat("\n")
} else if (x$approx.ci.lb == 1 & is.na(x$ci.lb) == FALSE) {
cat("Notes:")
cat("\n")
cat("- Approximation used for estimating ci.lb")
if (x$method == "P") {
cat("\n")
cat("- p-value approximated with normal distribution")
}
cat("\n")
cat("\n")
}
cat("===")
cat("\n")
cat("\n")
cat("Publication bias test p-uniform")
cat("\n")
cat("\n")
if (x$method == "LNP" | x$method == "LN1MINP" | x$method == "P" | x$method == "ML") {
x$pval.pb <- ifelse(x$pval.pb < 0.001, " <.001", round(x$pval.pb,
4))
print(format(data.frame(L.pb = round(x$L.pb, 4), pval = x$pval.pb,
row.names = ""), width = 9))
} else if (x$method == "P") {
cat("\n")
cat("p-value approximated with normal distribution")
cat("\n")
} else if (x$method == "KS" | x$method == "AD") {
cat("Publication bias test does not exist for method", x$method)
cat("\n")
}
cat("\n")
if (x$approx.pb == 1) {
cat("P(Z>=z) and P(Z>=zcv) were approximated")
}
cat("===")
cat("\n")
cat("\n")
cat("Fixed-effect meta-analysis")
cat("\n")
cat("\n")
x$Qpval <- ifelse(x$Qpval < 0.001, " <.001", round(x$Qpval, 4))
x$pval.fe <- ifelse(x$pval.fe < 0.001, " <.001", round(x$pval.fe,
4))
print(format(data.frame(est.fe = round(x$est.fe, 4), se.fe = round(x$se.fe, 4),
zval.fe = round(x$zval.fe, 4), pval.fe = x$pval.fe,
ci.lb.fe = round(x$ci.lb.fe, 4), ci.ub.fe = round(x$ci.ub.fe, 4),
Qstat = round(x$Qstat, 4), Qpval = x$Qpval, row.names = ""), width = 9))
cat("\n")
}
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