Running examples in ‘metafor-Ex.R’ failed
The error most likely occurred in:

> ### Name: update.rma
> ### Title: Model Updating for 'rma' Objects
> ### Aliases: update.rma
> ### Keywords: models
> 
> ### ** Examples
> 
> ### calculate log relative risks and corresponding sampling variances
> dat <- escalc(measure="RR", ai=tpos, bi=tneg, ci=cpos, di=cneg, data=dat.bcg)
> 
> ### random-effects model (method="REML" is default)
> res <- rma(yi, vi, data=dat, digits=3)
> res

Random-Effects Model (k = 13; tau^2 estimator: REML)

tau^2 (estimated amount of total heterogeneity): 0.313 (SE = 0.166)
tau (square root of estimated tau^2 value):      0.560
I^2 (total heterogeneity / total variability):   92.22%
H^2 (total variability / sampling variability):  12.86

Test for Heterogeneity: 
Q(df = 12) = 152.233, p-val < .001

Model Results:

estimate       se     zval     pval    ci.lb    ci.ub          
  -0.715    0.180   -3.974    <.001   -1.067   -0.362      *** 

---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

> 
> ### mixed-effects model with two moderators (absolute latitude and publication year)
> res <- update(res, ~ ablat + year)
> res

Mixed-Effects Model (k = 13; tau^2 estimator: REML)

tau^2 (estimated amount of residual heterogeneity):     0.111 (SE = 0.084)
tau (square root of estimated tau^2 value):             0.333
I^2 (residual heterogeneity / unaccounted variability): 71.98%
H^2 (unaccounted variability / sampling variability):   3.57
R^2 (amount of heterogeneity accounted for):            64.63%

Test for Residual Heterogeneity: 
QE(df = 10) = 28.325, p-val = 0.002

Test of Moderators (coefficient(s) 2,3): 
QM(df = 2) = 12.204, p-val = 0.002

Model Results:

         estimate      se    zval   pval    ci.lb   ci.ub    
intrcpt    -3.546  29.096  -0.122  0.903  -60.572  53.481    
ablat      -0.028   0.010  -2.737  0.006   -0.048  -0.008  **
year        0.002   0.015   0.130  0.897   -0.027   0.031    

---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

> 
> ### remove 'year' moderator
> res <- update(res, ~ . - year)
> res

Mixed-Effects Model (k = 13; tau^2 estimator: REML)

tau^2 (estimated amount of residual heterogeneity):     0.076 (SE = 0.059)
tau (square root of estimated tau^2 value):             0.276
I^2 (residual heterogeneity / unaccounted variability): 68.39%
H^2 (unaccounted variability / sampling variability):   3.16
R^2 (amount of heterogeneity accounted for):            75.62%

Test for Residual Heterogeneity: 
QE(df = 11) = 30.733, p-val = 0.001

Test of Moderators (coefficient(s) 2): 
QM(df = 1) = 16.357, p-val < .001

Model Results:

         estimate     se    zval   pval   ci.lb   ci.ub     
intrcpt     0.251  0.249   1.009  0.313  -0.237   0.740     
ablat      -0.029  0.007  -4.044  <.001  -0.043  -0.015  ***

---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

> 
> ### fit model with ML estimation
> update(res, method="ML")

Mixed-Effects Model (k = 13; tau^2 estimator: ML)

tau^2 (estimated amount of residual heterogeneity):     0.034 (SE = 0.028)
tau (square root of estimated tau^2 value):             0.185
I^2 (residual heterogeneity / unaccounted variability): 49.33%
H^2 (unaccounted variability / sampling variability):   1.97
R^2 (amount of heterogeneity accounted for):            87.73%

Test for Residual Heterogeneity: 
QE(df = 11) = 30.733, p-val = 0.001

Test of Moderators (coefficient(s) 2): 
QM(df = 1) = 28.911, p-val < .001

Model Results:

         estimate     se    zval   pval   ci.lb   ci.ub     
intrcpt     0.282  0.187   1.507  0.132  -0.085   0.649     
ablat      -0.030  0.005  -5.377  <.001  -0.040  -0.019  ***

---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

> 
> ### example with rma.glmm()
> res <- rma.glmm(measure="OR", ai=tpos, bi=tneg, ci=cpos, di=cneg, data=dat.bcg, digits=3)
> res <- update(res, mods = ~ ablat)

 *** caught segfault ***
address 7, cause 'memory not mapped'

Traceback:
 1: chol.default(H)
 2: chol(H)
 3: doTryCatch(return(expr), name, parentenv, handler)
 4: tryCatchOne(expr, names, parentenv, handlers[[1L]])
 5: tryCatchList(expr, classes, parentenv, handlers)
 6: tryCatch(chol(H), error = function(e) e)
 7: inherits(tryCatch(chol(H), error = function(e) e), "error")
 8: checkHess(derivs$Hessian, ccl$tol)
 9: checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv,     lbound = environment(devfun)$lower)
10: lme4::glmer(dat.grp ~ -1 + X.fit + study + (group12 - 1 | study),     offset = dat.off, family = dat.fam, nAGQ = nAGQ, verbose = verbose,     control = do.call(lme4::glmerControl, glmerCtrl))
11: doTryCatch(return(expr), name, parentenv, handler)
12: tryCatchOne(expr, names, parentenv, handlers[[1L]])
13: tryCatchList(expr, classes, parentenv, handlers)
14: tryCatch(expr, error = function(e) {    call <- conditionCall(e)    if (!is.null(call)) {        if (identical(call[[1L]], quote(doTryCatch)))             call <- sys.call(-4L)        dcall <- deparse(call)[1L]        prefix <- paste("Error in", dcall, ": ")        LONG <- 75L        msg <- conditionMessage(e)        sm <- strsplit(msg, "\n")[[1L]]        w <- 14L + nchar(dcall, type = "w") + nchar(sm[1L], type = "w")        if (is.na(w))             w <- 14L + nchar(dcall, type = "b") + nchar(sm[1L],                 type = "b")        if (w > LONG)             prefix <- paste0(prefix, "\n  ")    }    else prefix <- "Error : "    msg <- paste0(prefix, conditionMessage(e), "\n")    .Internal(seterrmessage(msg[1L]))    if (!silent && identical(getOption("show.error.messages"),         TRUE)) {        cat(msg, file = stderr())        .Internal(printDeferredWarnings())    }    invisible(structure(msg, class = "try-error", condition = e))})
15: try(lme4::glmer(dat.grp ~ -1 + X.fit + study + (group12 - 1 |     study), offset = dat.off, family = dat.fam, nAGQ = nAGQ,     verbose = verbose, control = do.call(lme4::glmerControl,         glmerCtrl)), silent = !verbose)
16: rma.glmm(ai = tpos, bi = tneg, ci = cpos, di = cneg, measure = "OR",     data = dat.bcg, digits = 3, mods = ~ablat)
17: eval(expr, envir, enclos)
18: eval(call, parent.frame())
19: update.rma(res, mods = ~ablat)
20: update(res, mods = ~ablat)
21: update(res, mods = ~ablat)
An irrecoverable exception occurred. R is aborting now ...