CRAN Package Check Results for Package metaSEM

Last updated on 2021-01-25 00:48:03 CET.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 1.2.5 16.69 188.75 205.44 OK
r-devel-linux-x86_64-debian-gcc 1.2.5 13.79 128.34 142.13 OK
r-devel-linux-x86_64-fedora-clang 1.2.5 237.34 OK
r-devel-linux-x86_64-fedora-gcc 1.2.5 215.12 OK
r-devel-windows-ix86+x86_64 1.2.5 34.00 200.00 234.00 OK
r-patched-linux-x86_64 1.2.5 15.93 158.13 174.06 OK
r-patched-solaris-x86 1.2.5 264.30 ERROR
r-release-linux-x86_64 1.2.5 17.09 158.55 175.64 OK
r-release-macos-x86_64 1.2.5 OK
r-release-windows-ix86+x86_64 1.2.5 36.00 201.00 237.00 OK
r-oldrel-macos-x86_64 1.2.5 OK
r-oldrel-windows-ix86+x86_64 1.2.5 27.00 199.00 226.00 OK

Check Details

Version: 1.2.5
Check: examples
Result: ERROR
    Running examples in ‘metaSEM-Ex.R’ failed
    The error most likely occurred in:
    
    > ### Name: BCG
    > ### Title: Dataset on the Effectiveness of the BCG Vaccine for Preventing
    > ### Tuberculosis
    > ### Aliases: BCG
    > ### Keywords: datasets
    >
    > ### ** Examples
    >
    > data(BCG)
    >
    > ## Univariate meta-analysis on the log of the odds ratio
    > summary( meta(y=ln_OR, v=v_ln_OR, data=BCG,
    + x=cbind(scale(Latitude,scale=FALSE),
    + scale(Year,scale=FALSE))) )
    
    Call:
    meta(y = ln_OR, v = v_ln_OR, x = cbind(scale(Latitude, scale = FALSE),
     scale(Year, scale = FALSE)), data = BCG)
    
    95% confidence intervals: z statistic approximation (robust=FALSE)
    Coefficients:
     Estimate Std.Error lbound ubound z value Pr(>|z|)
    Intercept1 -0.7166884 NA NA NA NA NA
    Slope1_1 -0.0335019 NA NA NA NA NA
    Slope1_2 -0.0013515 0.0043420 -0.0098616 0.0071587 -0.3113 0.7556
    Tau2_1_1 0.0020944 0.0043411 -0.0064141 0.0106029 0.4825 0.6295
    
    Q statistic on the homogeneity of effect sizes: 163.1649
    Degrees of freedom of the Q statistic: 12
    P value of the Q statistic: 0
    
    Explained variances (R2):
     y1
    Tau2 (no predictor) 0.3025
    Tau2 (with predictors) 0.0021
    R2 0.9931
    
    Number of studies (or clusters): 13
    Number of observed statistics: 13
    Number of estimated parameters: 4
    Degrees of freedom: 9
    -2 log likelihood: 13.89208
    OpenMx status1: 6 ("0" or "1": The optimization is considered fine.
    Other values may indicate problems.)
    Warning in print.summary.meta(x) :
     OpenMx status1 is neither 0 or 1. You are advised to 'rerun' it again.
    
    >
    > ## Multivariate meta-analysis on the log of the odds
    > ## The conditional sampling covariance is 0
    > bcg <- meta(y=cbind(ln_Odd_V, ln_Odd_NV), data=BCG,
    + v=cbind(v_ln_Odd_V, cov_V_NV, v_ln_Odd_NV))
    > summary(bcg)
    
    Call:
    meta(y = cbind(ln_Odd_V, ln_Odd_NV), v = cbind(v_ln_Odd_V, cov_V_NV,
     v_ln_Odd_NV), data = BCG)
    
    95% confidence intervals: z statistic approximation (robust=FALSE)
    Coefficients:
     Estimate Std.Error lbound ubound z value Pr(>|z|)
    Intercept1 -4.833744 NA NA NA NA NA
    Intercept2 -4.095975 0.171047 -4.431221 -3.760728 -23.9464 < 2.2e-16 ***
    Tau2_1_1 1.431371 0.156460 1.124714 1.738027 9.1485 < 2.2e-16 ***
    Tau2_2_1 1.757327 0.046092 1.666988 1.847665 38.1264 < 2.2e-16 ***
    Tau2_2_2 2.407333 0.266670 1.884669 2.929997 9.0274 < 2.2e-16 ***
    ---
    Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
    
    Q statistic on the homogeneity of effect sizes: 5270.386
    Degrees of freedom of the Q statistic: 24
    P value of the Q statistic: 0
    
    Heterogeneity indices (based on the estimated Tau2):
     Estimate
    Intercept1: I2 (Q statistic) 0.9887
    Intercept2: I2 (Q statistic) 0.9955
    
    Number of studies (or clusters): 13
    Number of observed statistics: 26
    Number of estimated parameters: 5
    Degrees of freedom: 21
    -2 log likelihood: 66.17587
    OpenMx status1: 6 ("0" or "1": The optimization is considered fine.
    Other values may indicate problems.)
    Warning in print.summary.meta(x) :
     OpenMx status1 is neither 0 or 1. You are advised to 'rerun' it again.
    
    >
    > plot(bcg)
    Warning in .solve(x = object$mx.fit@output$calculatedHessian, parameters = my.name) :
     Error in solving the Hessian matrix. Generalized inverse is used. The standard errors may not be trustworthy.
    
    Warning in sqrt(c(x[xind, xind], x[yind, yind])) : NaNs produced
    Error in if (scale[1] > 0) r <- r/scale[1] :
     missing value where TRUE/FALSE needed
    Calls: plot -> plot.meta -> points -> ellipse -> ellipse.default
    Execution halted
Flavor: r-patched-solaris-x86

Version: 1.2.5
Check: tests
Result: ERROR
     Running ‘testthat.R’ [22s/26s]
    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 279614612 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>
     Error in running mxModel:
     <simpleError: The job for model 'No predictor' exited abnormally with the error message: Non-conformable matrices in horizontal concatenation (cbind). First argument has 4 rows, and argument #2 has 0 rows.>
     Error: C stack usage 279614612 is too close to the limit
     <simpleError: The job for model 'TSSEM1 Correlation' exited abnormally with the error message: User interrupt>
     ══ Warnings ════════════════════════════════════════════════════════════════════
     ── Warning (test_utilities.R:568:5): metaFIML() works correctly ────────────────
     Error in solving the Hessian matrix. Generalized inverse is used. The standard errors may not be trustworthy.
    
     Backtrace:
     1. testthat::expect_equal(...) test_utilities.R:568:4
     6. metaSEM::vcov.meta(fit1a)
     7. metaSEM:::.solve(...)
     ── Warning (test_utilities.R:602:5): metaFIML() works correctly ────────────────
     Error in solving the Hessian matrix. Generalized inverse is used. The standard errors may not be trustworthy.
    
     Backtrace:
     1. stats::vcov(fit2a) test_utilities.R:602:4
     3. metaSEM::vcov.meta(fit2a)
     4. metaSEM:::.solve(...)
     ── Warning (test_utilities.R:642:5): metaFIML() works correctly ────────────────
     Error in solving the Hessian matrix. Generalized inverse is used. The standard errors may not be trustworthy.
    
     Backtrace:
     1. testthat::expect_equal(...) test_utilities.R:642:4
     6. metaSEM::vcov.meta(fit3a)
     7. metaSEM:::.solve(...)
    
     ══ Failed tests ════════════════════════════════════════════════════════════════
     ── Error (test_utilities.R:336:5): Cor2DataFrame() works correctly ─────────────
     Error: The job for model 'Asymptotic covariance matrix of correlation matrix' exited abnormally with the error message: User interrupt
     Backtrace:
     █
     1. └─metaSEM::Cor2DataFrame(Nohe15A1$data, Nohe15A1$n) test_utilities.R:336:4
     2. └─metaSEM::asyCov(...)
     3. └─base::mapply(...)
     4. └─(function (x, n, cor.analysis = TRUE, dropNA = FALSE, as.matrix = TRUE, ...
     ── Failure (test_utilities.R:604:5): metaFIML() works correctly ────────────────
     `v_fit2a` not equal to `v_fit2b`.
     11/64 mismatches (average diff: 0.556)
     [19] 4.06e-06 - 0.02166 == -0.02165
     [20] 3.74e-06 - -0.01952 == 0.01952
     [24] 5.14e-08 - -0.01066 == 0.01066
     [27] 3.74e-06 - -0.01952 == 0.01952
     [28] 3.45e-06 - 0.04903 == -0.04903
     [32] 4.73e-08 - -0.04581 == 0.04581
     [48] 8.22e-08 - -0.00822 == 0.00822
     [59] 5.14e-08 - -0.01066 == 0.01066
     [60] 4.73e-08 - -0.04581 == 0.04581
     ...
     ── Error (test_utilities.R:666:5): Handling NA in diagonals in tssem1FEM() correctly ──
     Error: The job for model 'TSSEM1 Correlation' exited abnormally with the error message: User interrupt
     Backtrace:
     █
     1. └─metaSEM::tssem1(Cov = list(C1, C2, C3), n = c(50, 50, 50), method = "FEM") test_utilities.R:666:4
     2. └─metaSEM::tssem1FEM(...)
    
     [ FAIL 3 | WARN 3 | SKIP 0 | PASS 97 ]
     Error: Test failures
     Execution halted
Flavor: r-patched-solaris-x86