### Sample 1: paper medians with bootstrap variance (n = 88)

====== p-uniform* null=0 right-sided ======
[P method failed; retrying with LNP]
[1] "Error in if (est.l > 0 & est.u < 0) { : \n  missing value where TRUE/FALSE needed\n"
attr(,"class")
[1] "try-error"
attr(,"condition")
<simpleError in if (est.l > 0 & est.u < 0) {    break}: missing value where TRUE/FALSE needed>

====== p-uniform* null=0 left-sided ======
[P method failed; retrying with LNP]
[1] "Error in if (est.l > 0 & est.u < 0) { : \n  missing value where TRUE/FALSE needed\n"
attr(,"class")
[1] "try-error"
attr(,"condition")
<simpleError in if (est.l > 0 & est.u < 0) {    break}: missing value where TRUE/FALSE needed>

====== p-uniform* null=2 right-sided ======
[P method failed; retrying with LNP]
[1] "Error in if (est.l > 0 & est.u < 0) { : \n  missing value where TRUE/FALSE needed\n"
attr(,"class")
[1] "try-error"
attr(,"condition")
<simpleError in if (est.l > 0 & est.u < 0) {    break}: missing value where TRUE/FALSE needed>

====== p-uniform* null=2 left-sided ======
[P method failed; retrying with LNP]
[1] "Error in if (method == \"P\" & tau0 <= 0 | method == \"LNP\" & tau0 >= 0) { : \n  missing value where TRUE/FALSE needed\n"
attr(,"class")
[1] "try-error"
attr(,"condition")
<simpleError in if (method == "P" & tau0 <= 0 | method == "LNP" & tau0 >= 0) {    tau.est <- 0    est <- try(uniroot(pdist_nsig, interval = c(int[1], int[2]),         tau = tau.est, yi = yi, vi = vi, param = "est", ycv = ycv,         method = method, val = "es", cv_P = 0)$root, silent = TRUE)    if (inherits(est, what = "try-error")) {        est <- NA        tau.est <- NA    }    break}: missing value where TRUE/FALSE needed>

### Sample 2: genuine CI-derived SE (n = 16)

====== p-uniform* null=0 right-sided ======

Method: P (k = 16; ksig = 13)

Estimating effect size p-uniform*

       est     ci.lb     ci.ub       L.0      pval
    1.0886    0.7775    1.4095        NA        NA

Note:
- Test of no effect is not available for method P

===

Estimating between-study variance p-uniform*

      tau2   tau2.lb   tau2.ub     L.het    pval pval.boot
    0.1658    0.0485     0.559       Inf   <.001        NA

====== p-uniform* null=0 left-sided ======

Method: P (k = 16; ksig = 0)

Estimating effect size p-uniform*

       est     ci.lb     ci.ub       L.0      pval
    0.9662    0.6225    1.2907        NA        NA

Note:
- Test of no effect is not available for method P

===

Estimating between-study variance p-uniform*

      tau2   tau2.lb   tau2.ub     L.het    pval pval.boot
    0.2899    0.0411    1.3856       Inf   <.001        NA

====== p-uniform* null=2 right-sided ======

Method: P (k = 16; ksig = 0)

Estimating effect size p-uniform*

       est     ci.lb     ci.ub       L.0      pval
   -1.0065   -1.3172   -0.6771        NA        NA

Note:
- Test of no effect is not available for method P

===

Estimating between-study variance p-uniform*

      tau2   tau2.lb   tau2.ub     L.het    pval pval.boot
    0.2783    0.0402    1.0671       Inf   <.001        NA

====== p-uniform* null=2 left-sided ======

Method: P (k = 16; ksig = 11)

Estimating effect size p-uniform*

       est     ci.lb     ci.ub       L.0      pval
   -1.2797   -1.5779   -1.0048        NA        NA

Note:
- Test of no effect is not available for method P

===

Estimating between-study variance p-uniform*

      tau2   tau2.lb   tau2.ub     L.het    pval pval.boot
    0.1602    0.0525    0.4646       Inf   <.001        NA
