Running ‘testthat.R’ [16s/46s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > library(testthat)
  > library(metaSEM)
  Loading required package: OpenMx
  To take full advantage of multiple cores, use:
    mxOption(key='Number of Threads', value=parallel::detectCores()) #now
    Sys.setenv(OMP_NUM_THREADS=parallel::detectCores()) #before library(OpenMx)
  "SLSQP" is set as the default optimizer in OpenMx.
  mxOption(NULL, "Gradient algorithm") is set at "central".
  mxOption(NULL, "Optimality tolerance") is set at "6.3e-14".
  mxOption(NULL, "Gradient iterations") is set at "2".
  > 
  > test_check("metaSEM")
  Error: C stack usage  279745684 is too close to the limit
  <simpleError: The job for model 'Asymptotic covariance matrix of correlation matrix' exited abnormally with the error message: User interrupt>
  
   *** caught segfault ***
  address 0, cause 'memory not mapped'
  
  Traceback:
   1: runHelper(model, frontendStart, intervals, silent, suppressWarnings,     unsafe, checkpoint, useSocket, onlyFrontend, useOptimizer,     beginMessage)
   2: (function (model, ..., intervals = NULL, silent = FALSE, suppressWarnings = FALSE,     unsafe = FALSE, checkpoint = FALSE, useSocket = FALSE, onlyFrontend = FALSE,     useOptimizer = TRUE, beginMessage = !silent) {    warnModelCreatedByOldVersion(model)    if (is.null(intervals)) {    }    else if (length(intervals) != 1 || typeof(intervals) != "logical" ||         is.na(intervals)) {        stop(paste("'intervals' argument", "must be TRUE or FALSE in",             deparse(width.cutoff = 400L, sys.call())), call. = FALSE)    }    frontendStart <- Sys.time()    prohibitDotdotdot(list(...))    runHelper(model, frontendStart, intervals, silent, suppressWarnings,         unsafe, checkpoint, useSocket, onlyFrontend, useOptimizer,         beginMessage)})(new("MxModel", name = "mxModel", matrices = list(Amatrix = new("FullMatrix",     name = "Amatrix", values = c(0, 0, 0, 0, 0, 0, 0, 0, 1, 0,     0, 0, 0, 1, 0, 0), labels = c(NA, NA, NA, NA, NA, NA, NA,     NA, NA, NA, NA, NA, NA, NA, "Slope1_1", NA), free = c(FALSE,     FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,     FALSE, FALSE, FALSE, FALSE, TRUE, FALSE), lbound = c(NA_real_,     NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,     NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,     NA_real_, NA_real_, NA_real_), ubound = c(NA_real_, NA_real_,     NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,     NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,     NA_real_, NA_real_), .squareBrackets = numeric(0), .persist = TRUE,     .condenseSlots = FALSE, display = character(0), dependencies = integer(0),     joinModel = NA_character_, joinKey = NA_character_), Smatrix = new("FullMatrix",     name = "Smatrix", values = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0,     0, 0, 0, 0, 0, 0), labels = c("data.r_v", NA, NA, NA, NA,     NA, NA, NA, NA, NA, "Tau2_1_1", NA, NA, NA, NA, "CovX1_X1"    ), free = c(FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,     FALSE, FALSE, FALSE, TRUE, FALSE, FALSE, FALSE, FALSE, TRUE    ), lbound = c(NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,     NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,     NA_real_, NA_real_, NA_real_, NA_real_, NA_real_), ubound = c(NA_real_,     NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,     NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,     NA_real_, NA_real_, NA_real_), .squareBrackets = numeric(0),     .persist = TRUE, .condenseSlots = FALSE, display = character(0),     dependencies = integer(0), joinModel = NA_character_, joinKey = NA_character_),     Fmatrix = new("FullMatrix", name = "Fmatrix", values = c(1,     0, 0, 1, 0, 0, 0, 0), labels = c(NA_character_, NA_character_,     NA_character_, NA_character_, NA_character_, NA_character_,     NA_character_, NA_character_), free = c(FALSE, FALSE, FALSE,     FALSE, FALSE, FALSE, FALSE, FALSE), lbound = c(NA_real_,     NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,     NA_real_), ubound = c(NA_real_, NA_real_, NA_real_, NA_real_,     NA_real_, NA_real_, NA_real_, NA_real_), .squareBrackets = numeric(0),         .persist = TRUE, .condenseSlots = FALSE, display = character(0),         dependencies = integer(0), joinModel = NA_character_,         joinKey = NA_character_), Mmatrix = new("FullMatrix",         name = "Mmatrix", values = c(0, 0, 0, 0), labels = c(NA,         NA, "Intercept1", "MeanX1"), free = c(FALSE, FALSE, TRUE,         TRUE), lbound = c(NA_real_, NA_real_, NA_real_, NA_real_        ), ubound = c(NA_real_, NA_real_, NA_real_, NA_real_),         .squareBrackets = numeric(0), .persist = TRUE, .condenseSlots = FALSE,         display = character(0), dependencies = integer(0), joinModel = NA_character_,         joinKey = NA_character_)), algebras = list(Sfull = new("MxAlgebra",     formula = Smatrix, name = "Sfull", fixed = FALSE, .dimnames = NULL,     result = numeric(0), joinModel = NA_character_, joinKey = NA_character_,     verbose = 0L, initial = NA_real_)), constraints = list(),     intervals = list(Amatrix = new("MxInterval", reference = "Amatrix",         lowerdelta = 3.84145882069412, upperdelta = 3.84145882069412,         boundAdj = TRUE), Smatrix = new("MxInterval", reference = "Smatrix",         lowerdelta = 3.84145882069412, upperdelta = 3.84145882069412,         boundAdj = TRUE), Mmatrix = new("MxInterval", reference = "Mmatrix",         lowerdelta = 3.84145882069412, upperdelta = 3.84145882069412,         boundAdj = TRUE)), latentVars = character(0), manifestVars = character(0),     data = new("MxDataStatic", observed = list(Author = c("Aryee et al. (2002)",     "Balfour and Wechsler (1991)", "Bashaw and Grant (1994)",     "Benkhoff (1997)", "Brett et al. (1995)", "Brett et al. (1995)",     "Chen et al. (2002)", "Chow et al. (2002)", "Dubinsky et al. (1997)",     "Dubinsky et al. (1997)", "Dubinsky and Skinner (1984)",     "Dubinsky et al. (1992)", "Dubinsky et al. (1992)", "Dubinsky et al. (1992)",     "Evans et al. (1995)", "Ferris (1981)", "Ferris (1981)",     "Fletcher and Williams (1996)", "Ganster and Dwyer (1995)",     "Ganster and Dwyer (1995)", "Goffin and Gellatly (2001)",     "Grant and Cr_vens (2001)", "Griffin (1991)", "Hampton et al. (1986)",     "Ingram et al. (1989)", "Ingram and Lee (1990)", "Ivancevich and McMahon (1982)",     "Joshi and Randall (2001)", "Keller (1997)", "Lee and Mowday (1987)",     "Leong et al. (1994)", "Levy and Williams (1998)", "Levy and Williams (1998)",     "Low (2001)", "Mathieu and Farr (1991)", "MacKenzie et al. (1998)",     "McNeily and Russ (1992)", "Meyer and Smith (2000)", "Meyer et al. (1989)",     "Morrison (1997)", "Nouri and Parker (1998)", "Orpen (1997)",     "Parasuraman (1984)", "Pierce et al. (1989)", "Pierce et al. (1989)",     "Pierce et al. (1989)", "Russ and McNeily (1995)", "Russ and McNeily (1995)",     "Ruyter et al. (2001)", "Sager and Johnston (1989)", "Siders et al. (2001)",     "Singh (1998)", "Singh et al. (1994)", "Somers and Birnbaum (1998)",     "Steers (1977)", "Stumpf and Hartman (1984)", "Suliman and Iles (2000)",     "Tang and Sarsfield-Baldwin (1996)", "Vigoda (2002)", "Wiener and Vardi (1980)",     "Yousef (2000)"), Sample_size = c(179L, 232L, 560L, 181L,     156L, 180L, 253L, 790L, 218L, 220L, 116L, 218L, 220L, 156L,     81L, 123L, 46L, 860L, 512L, 172L, 79L, 148L, 526L, 116L,     231L, 120L, 209L, 151L, 532L, 445L, 308L, 62L, 46L, 80L,     311L, 672L, 58L, 277L, 65L, 307L, 135L, 39L, 217L, 116L,     188L, 96L, 77L, 76L, 154L, 132L, 328L, 518L, 377L, 109L,     382L, 85L, 45L, 90L, 303L, 56L, 430L), Sales = c("mixed",     "nonsales", "sales", "sales", "sales", "sales", "nonsales",     "nonsales", "sales", "sales", "sales", "sales", "sales",     "sales", "sales", "nonsales", "nonsales", "mixed", "nonsales",     "nonsales", "nonsales", "sales", "nonsales", "sales", "sales",     "sales", "nonsales", "sales", "nonsales", "nonsales", "sales",     "mixed", "mixed", "sales", "nonsales", "sales", "sales",     "nonsales", "nonsales", "sales", "nonsales", "mixed", "nonsales",     "sales", "nonsales", "nonsales", "sales", "sales", "nonsales",     "sales", "sales", "sales", "nonsales", "nonsales", "nonsales",     "nonsales", "nonsales", "nonsales", "nonsales", "sales",     "mixed"), Country = c("India", "USA", "USA", "Germany", "USA",     "USA", "China", "Taiwan", "USA", "Japan", "USA", "USA", "Japan",     "South Korea", "USA", "USA", "USA", "UK", "USA", "USA", "Canada",     "Australia", "USA", "USA", "USA", "USA", "USA", "USA", "USA",     "USA", "Singapore", "USA", "USA", "Australia", "USA", "USA",     "USA", "Canada", "Canada", "USA", "USA", "UK", "USA", "USA",     "USA", "USA", "USA", "USA", "USA", "USA", "USA", "USA", "USA",     "USA", "USA", "USA", "Jordan", "USA", "Israel", "USA", "UAE"    ), IDV = c(48L, 91L, 91L, 67L, 91L, 91L, 53L, 53L, 91L, 46L,     91L, 91L, 46L, 18L, 91L, 91L, 91L, 89L, 91L, 91L, 80L, 90L,     91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 20L, 91L, 91L, 90L,     91L, 91L, 91L, 80L, 80L, 91L, 91L, 89L, 91L, 91L, 91L, 91L,     91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 38L, 91L,     54L, 91L, 38L), OC_scale = c("Porter or Mowday", "other",     "Porter or Mowday", "Porter or Mowday", "Porter or Mowday",     "Porter or Mowday", "Porter or Mowday", "Meyer", "Porter or Mowday",     "Porter or Mowday", "other", "Porter or Mowday", "Porter or Mowday",     "Porter or Mowday", "other", "other", "other", "other", "Porter or Mowday",     "Porter or Mowday", "Meyer", "Porter or Mowday", "Porter or Mowday",     "other", "Porter or Mowday", "Porter or Mowday", "Porter or Mowday",     "Porter or Mowday", "Porter or Mowday", "Porter or Mowday",     "Porter or Mowday", "Meyer", "Meyer", "Porter or Mowday",     "Porter or Mowday", "Porter or Mowday", "Porter or Mowday",     "Meyer", "Meyer", "Porter or Mowday", "Porter or Mowday",     "Meyer", "other", "Porter or Mowday", "Porter or Mowday",     "Porter or Mowday", "Porter or Mowday", "Porter or Mowday",     "Porter or Mowday", "Porter or Mowday", "other", "Porter or Mowday",     "Porter or Mowday", "Meyer", "Porter or Mowday", "Porter or Mowday",     "Meyer", "Porter or Mowday", "Porter or Mowday", "other",     "Porter or Mowday"), OC_alpha = c(0.87, 0.82, 0.83, NA, 0.83,     0.83, 0.87, 0.81, 0.92, 0.86, 0.8, 0.89, 0.84, 0.87, 0.86,     NA, NA, NA, 0.87, 0.88, NA, 0.9, 0.87, 0.8, 0.91, 0.87, 0.87,     0.92, 0.76, NA, 0.75, 0.88, 0.88, 0.9, 0.87, 0.87, 0.87,     0.78, 0.72, 0.85, 0.89, NA, 0.88, 0.89, 0.89, 0.89, 0.92,     0.92, 0.93, 0.87, 0.77, 0.83, 0.79, 0.76, 0.88, 0.85, 0.66,     0.92, 0.88, 0.72, 0.81), JP_alpha = c(0.89, NA, 0.76, 1,     NA, NA, 0.8, 0.91, 0.81, 0.9, NA, 0.81, 0.9, 0.93, 0.85,     NA, NA, NA, NA, NA, NA, 0.84, 0.92, NA, 0.78, 0.98, 0.81,     0.91, 0.91, NA, 0.75, NA, NA, 0.84, 0.87, 0.89, 0.89, 0.93,     0.87, NA, NA, NA, 0.85, NA, 0.82, NA, 0.91, 0.91, 0.93, 0.95,     NA, 0.74, 0.84, NA, NA, 0.93, 0.84, NA, NA, NA, 0.8), r = c(0.02,     0.12, 0.09, 0.2, 0.08, 0.04, 0.15, 0.45, 0.24, 0.23, 0.2,     0.23, 0.3, 0.32, 0.42, 0.04, 0.01, 0.15, 0.06, 0.14, -0.01,     0.35, 0.03, -0.05, 0.17, 0.26, 0.04, 0.25, 0.06, 0.09, 0.13,     0.3, -0.16, 0.35, 0.13, 0.14, 0.19, 0.34, -0.03, 0.3, 0.35,     0.2, 0.05, 0.17, -0.06, 0.11, 0.52, 0.52, 0.34, 0.23, 0.2,     0.26, 0.08, 0.06, 0.05, 0.62, 0.49, 0.19, 0.09, 0.05, 0.28    ), r_v = c(0.00558212379888268, 0.00418710068965517, 0.001756902875,     0.00509171270718232, 0.00632846769230769, 0.005537792, 0.00377670454545455,     0.000805071202531646, 0.00407393467889908, 0.0040772655,     0.0079448275862069, 0.00411467160550459, 0.00376409090909091,     0.00516465230769231, 0.00837428345679012, 0.00810408585365853,     0.021734782826087, 0.00111105377906977, 0.0019390878125,     0.00558828, 0.0126556963291139, 0.00520274493243243, 0.00189772017110266,     0.0085776400862069, 0.00408240350649351, 0.007244748, 0.00476939023923445,     0.00582057119205298, 0.00186618977443609, 0.00221093395505618,     0.00313794029220779, 0.0133564516129032, 0.0206403339130435,     0.009625078125, 0.00310767077170418, 0.00143033357142857,     0.016019020862069, 0.00282369444043321, 0.0153569355384615,     0.00269739413680782, 0.00570375, 0.0236307692307692, 0.00458528225806452,     0.00812961387931034, 0.00528092, 0.0101661084375, 0.00691319688311688,     0.00700416, 0.00507898285714286, 0.0067954425, 0.00280975609756098,     0.00167832, 0.00261867628647215, 0.00910837577981651, 0.00260472840314136,     0.00445839247058823, 0.012832178, 0.010323369, 0.00324708122112211,     0.01776796875, 0.00197522455813953)), means = NA_real_, type = "raw",         numObs = 61, observedStats = list(), .isSorted = FALSE,         .needSort = TRUE, .parallel = TRUE, .noExoOptimize = TRUE,         primaryKey = NA_character_, weight = NA_character_, frequency = NA_character_,         minVariance = 1.49011611938477e-08, algebra = character(0),         warnNPDacov = TRUE, exoFree = NULL, naAction = "pass",         verbose = 0L, name = "data"), submodels = list(), expectation = new("MxExpectationRAM",         A = "Amatrix", S = "Sfull", F = "Fmatrix", M = "Mmatrix",         thresholds = NA_character_, dims = c("r", "JP_alpha",         "fy", "fx"), usePPML = FALSE, ppmlData = NULL, UnfilteredExpCov = NA,         numStats = numeric(0), between = NULL, isProductNode = NULL,         verbose = 0L, .rampartCycleLimit = NA_integer_, .rampartUnitLimit = NA_integer_,         .useSufficientSets = TRUE, .forceSingleGroup = FALSE,         .analyzeDefVars = TRUE, .maxDebugGroups = 0L, .optimizeMean = 2L,         .useSparse = NA, expectedCovariance = NULL, expectedMean = NULL,         threshnames = c("r", "JP_alpha", "fy", "fx"), discrete = NA_character_,         discreteSpec = NULL, .discreteCheckCount = TRUE, data = NA_integer_,         dataColumns = integer(0), dataColumnNames = NULL, .runDims = character(0),         output = list(), debug = list(), name = "expectation"),     fitfunction = new("MxFitFunctionML", fellner = NA, verbose = 0L,         profileOut = character(0), rowwiseParallel = NA, jointConditionOn = "auto",         components = character(0), info = list(), dependencies = integer(0),         expectation = integer(0), vector = FALSE, rowDiagnostics = FALSE,         result = numeric(0), name = "fitfunction"), compute = NULL,     independent = FALSE, options = list(), output = list(), runstate = list(),     .newobjects = FALSE, .resetdata = FALSE, .wasRun = FALSE,     .modifiedSinceRun = TRUE, .version = "2.18.1"), intervals = FALSE,     suppressWarnings = TRUE, silent = TRUE)
   3: do.call(mxRun, c(list(mx.model, intervals = intervals, suppressWarnings = suppressWarnings,     silent = silent), mxRun.Args))
   4: create.mxModel(RAM = RAM1, data = Jaramillo05)
   5: eval(code, test_env)
   6: eval(code, test_env)
   7: withCallingHandlers({    eval(code, test_env)    if (!handled && !is.null(test)) {        skip_empty()    }}, expectation = handle_expectation, skip = handle_skip, warning = handle_warning,     message = handle_message, error = handle_error)
   8: doTryCatch(return(expr), name, parentenv, handler)
   9: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  10: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
  11: doTryCatch(return(expr), name, parentenv, handler)
  12: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]),     names[nh], parentenv, handlers[[nh]])
  13: tryCatchList(expr, classes, parentenv, handlers)
  14: tryCatch(withCallingHandlers({    eval(code, test_env)    if (!handled && !is.null(test)) {        skip_empty()    }}, expectation = handle_expectation, skip = handle_skip, warning = handle_warning,     message = handle_message, error = handle_error), error = handle_fatal,     skip = function(e) {    })
  15: test_code(desc, code, env = parent.frame(), reporter = reporter)
  16: test_that("metaFIML() works correctly", {    fit1a <- metaFIML(y = r, v = r_v, x = JP_alpha, data = Jaramillo05)    m1 <- "fy =~ 1*r\n           r ~~ data.r_v*r\n           fx =~ 1*JP_alpha\n           JP_alpha ~~ 0*JP_alpha\n           fy ~ Slope1_1*fx\n           fy ~~ Tau2_1_1*fy\n           fx ~~ CovX1_X1*fx\n           fx ~ MeanX1*1\n           fy ~ Intercept1*1"    RAM1 <- lavaan2RAM(m1, obs.variables = c("r", "JP_alpha"),         std.lv = FALSE)    fit1b <- create.mxModel(RAM = RAM1, data = Jaramillo05)    coef1a <- coef(fit1a)    names1 <- names(coef1a)    coef1b <- coef(fit1b)[names1]    tolerance <- 0.001    expect_equal(coef1a, coef1b, tolerance = tolerance)    expect_equal(vcov(fit1a), vcov(fit1b)[names1, names1], tolerance = tolerance)    expect_equal(fit1a$mx.fit$output$Minus2LogLikelihood, fit1b$output$Minus2LogLikelihood)    fit2a <- metaFIML(y = r, v = r_v, x = JP_alpha, av = IDV,         data = Jaramillo05)    m2 <- "fy =~ 1*r\n           r ~~ data.r_v*r\n           fx =~ 1*JP_alpha\n           JP_alpha ~~ 0*JP_alpha\n           fy ~ Slope1_1*fx\n           fy ~~ Tau2_1_1*fy\n           fx ~~ CovX1_X1*fx\n           fx ~ MeanX1*1\n           fy ~ Intercept1*1\n\n           fz =~ 1*IDV\n           IDV ~~ 0*IDV\n           fz ~ MeanX2*1\n           fz ~~ CovX2_X2*fz + start(818)*fz\n           fx ~~ CovX2_X1*fz\n           fy ~~ CovX2_Y1*fz"    RAM2 <- lavaan2RAM(m2, obs.variables = c("r", "JP_alpha",         "IDV"), std.lv = FALSE)    fit2b <- create.mxModel(RAM = RAM2, data = Jaramillo05)    coef2a <- coef(fit2a)    names2 <- names(coef2a)    coef2b <- coef(fit2b)[names2]    expect_equal(coef2a, coef2b, tolerance = tolerance)    v_fit2a <- vcov(fit2a)[-4, -4]    v_fit2b <- vcov(fit2b)[names2, names2][-4, -4]    expect_equal(v_fit2a, v_fit2b, tolerance = tolerance)    expect_equal(fit2a$mx.fit$output$Minus2LogLikelihood, fit2b$output$Minus2LogLikelihood)    wvs94a$gnp <- scale(wvs94a$gnp)    fit3a <- metaFIML(y = cbind(lifesat, lifecon), v = cbind(lifesat_var,         inter_cov, lifecon_var), x = gnp, data = wvs94a)    m3 <- "fy1 =~ 1*lifesat\n           lifesat ~~ data.lifesat_var*lifesat\n           fy2 =~ 1*lifecon\n           lifecon ~~ data.lifecon_var*lifecon\n           lifesat ~~ data.inter_cov*lifecon\n\n           fx =~ 1*gnp\n           gnp ~~ 0*gnp\n           fy1 ~ Slope1_1*fx\n           fy2 ~ Slope2_1*fx\n\n           fy1 ~~ Tau2_1_1*fy1\n           fy2 ~~ Tau2_2_2*fy2\n           fy1 ~~ Tau2_2_1*fy2\n           fx ~~ CovX1_X1*fx\n           fx ~ MeanX1*1\n           fy1 ~ Intercept1*1\n           fy2 ~ Intercept2*1"    RAM3 <- lavaan2RAM(m3, obs.variables = c("lifesat", "lifecon",         "gnp"), std.lv = FALSE)    fit3b <- create.mxModel(RAM = RAM3, data = wvs94a)    coef3a <- coef(fit3a)    names3 <- names(coef3a)    coef3b <- coef(fit3b)[names3]    expect_equal(coef3a, coef3b, tolerance = tolerance)    expect_equal(vcov(fit3a), vcov(fit3b)[names3, names3], tolerance = tolerance)    expect_equal(fit3a$mx.fit$output$Minus2LogLikelihood, fit3b$output$Minus2LogLikelihood)})
  17: eval(code, test_env)
  18: eval(code, test_env)
  19: withCallingHandlers({    eval(code, test_env)    if (!handled && !is.null(test)) {        skip_empty()    }}, expectation = handle_expectation, skip = handle_skip, warning = handle_warning,     message = handle_message, error = handle_error)
  20: doTryCatch(return(expr), name, parentenv, handler)
  21: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  22: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
  23: doTryCatch(return(expr), name, parentenv, handler)
  24: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]),     names[nh], parentenv, handlers[[nh]])
  25: tryCatchList(expr, classes, parentenv, handlers)
  26: tryCatch(withCallingHandlers({    eval(code, test_env)    if (!handled && !is.null(test)) {        skip_empty()    }}, expectation = handle_expectation, skip = handle_skip, warning = handle_warning,     message = handle_message, error = handle_error), error = handle_fatal,     skip = function(e) {    })
  27: test_code(NULL, exprs, env)
  28: source_file(path, child_env(env), wrap = wrap)
  29: FUN(X[[i]], ...)
  30: lapply(test_paths, test_one_file, env = env, wrap = wrap)
  31: force(code)
  32: doWithOneRestart(return(expr), restart)
  33: withOneRestart(expr, restarts[[1L]])
  34: withRestarts(testthat_abort_reporter = function() NULL, force(code))
  35: with_reporter(reporters$multi, lapply(test_paths, test_one_file,     env = env, wrap = wrap))
  36: test_files(test_dir = test_dir, test_package = test_package,     test_paths = test_paths, load_helpers = load_helpers, reporter = reporter,     env = env, stop_on_failure = stop_on_failure, stop_on_warning = stop_on_warning,     wrap = wrap, load_package = load_package)
  37: test_files(test_dir = path, test_paths = test_paths, test_package = package,     reporter = reporter, load_helpers = load_helpers, env = env,     stop_on_failure = stop_on_failure, stop_on_warning = stop_on_warning,     wrap = wrap, load_package = load_package, parallel = parallel)
  38: test_dir("testthat", package = package, reporter = reporter,     ..., load_package = "installed")
  39: test_check("metaSEM")
  An irrecoverable exception occurred. R is aborting now ...