CRAN Package Check Results for Package metaSEM

Last updated on 2020-11-01 01:47:26 CET.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 1.2.4 18.19 163.28 181.47 OK
r-devel-linux-x86_64-debian-gcc 1.2.4 15.01 116.93 131.94 OK
r-devel-linux-x86_64-fedora-clang 1.2.4 229.78 OK
r-devel-linux-x86_64-fedora-gcc 1.2.4 213.67 OK
r-devel-windows-ix86+x86_64 1.2.4 33.00 192.00 225.00 OK
r-patched-linux-x86_64 1.2.4 17.03 144.46 161.49 OK
r-patched-solaris-x86 1.2.4 264.40 ERROR
r-release-linux-x86_64 1.2.4 15.56 143.68 159.24 OK
r-release-macos-x86_64 1.2.4 OK
r-release-windows-ix86+x86_64 1.2.4 30.00 202.00 232.00 OK
r-oldrel-macos-x86_64 1.2.4 OK
r-oldrel-windows-ix86+x86_64 1.2.4 31.00 129.00 160.00 OK

Check Details

Version: 1.2.4
Check: examples
Result: ERROR
    Running examples in ‘metaSEM-Ex.R’ failed
    The error most likely occurred in:
    
    > ### Name: Berkey98
    > ### Title: Five Published Trails from Berkey et al. (1998)
    > ### Aliases: Berkey98
    > ### Keywords: datasets
    >
    > ### ** Examples
    >
    > data(Berkey98)
    >
    > #### ML estimation method
    > ## Multivariate meta-analysis
    > x <- meta(y=cbind(PD, AL), v=cbind(var_PD, cov_PD_AL, var_AL), data=Berkey98)
    > x <- rerun(x)
    Running Meta analysis with ML with 5 parameters
    
    Beginning initial fit attempt
    Running Meta analysis with ML with 5 parameters
    
    Solution found
    
    
    
    
     Solution found! Final fit=-11.681314 (started at -11.681314) (1 attempt(s): 1 valid, 0 errors)
    
    > summary(x)
    
    Call:
    meta(y = cbind(PD, AL), v = cbind(var_PD, cov_PD_AL, var_AL),
     data = Berkey98)
    
    95% confidence intervals: z statistic approximation (robust=FALSE)
    Coefficients:
     Estimate Std.Error lbound ubound z value Pr(>|z|)
    Intercept1 0.3448392 0.0536312 0.2397239 0.4499544 6.4298 1.278e-10 ***
    Intercept2 -0.3379381 0.0812480 -0.4971812 -0.1786951 -4.1593 3.192e-05 ***
    Tau2_1_1 0.0070020 0.0090497 -0.0107351 0.0247391 0.7737 0.4391
    Tau2_2_1 0.0094607 0.0099698 -0.0100797 0.0290010 0.9489 0.3427
    Tau2_2_2 0.0261445 0.0177409 -0.0086270 0.0609161 1.4737 0.1406
    ---
    Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
    
    Q statistic on the homogeneity of effect sizes: 128.2267
    Degrees of freedom of the Q statistic: 8
    P value of the Q statistic: 0
    
    Heterogeneity indices (based on the estimated Tau2):
     Estimate
    Intercept1: I2 (Q statistic) 0.6021
    Intercept2: I2 (Q statistic) 0.9250
    
    Number of studies (or clusters): 5
    Number of observed statistics: 10
    Number of estimated parameters: 5
    Degrees of freedom: 5
    -2 log likelihood: -11.68131
    OpenMx status1: 0 ("0" or "1": The optimization is considered fine.
    Other values may indicate problems.)
    > plot(x)
    >
    > ## Plot individual studies proportional to the weights
    > plot(x, study.weight.plot=TRUE)
    >
    > ## Include forest plot from the metafor package
    > library(metafor)
    Loading required package: Matrix
    
    Attaching package: ‘Matrix’
    
    The following objects are masked from ‘package:OpenMx’:
    
     %&%, expm
    
    Loading 'metafor' package (version 2.4-0). For an overview
    and introduction to the package please type: help(metafor).
    > plot(x, diag.panel=TRUE, main="Multivariate meta-analysis",
    + axis.label=c("PD", "AL"))
    > forest( rma(yi=PD, vi=var_PD, data=Berkey98) )
    > title("Forest plot of PD")
    > forest( rma(yi=AL, vi=var_AL, data=Berkey98) )
    > title("Forest plot of AL")
    >
    > ## Multivariate meta-analysis with "publication year-1979" as the predictor
    > summary( meta(y=cbind(PD, AL), v=cbind(var_PD, cov_PD_AL, var_AL),
    + x=scale(pub_year, center=1979), data=Berkey98,
    + RE.lbound=NA) )
    
    Call:
    meta(y = cbind(PD, AL), v = cbind(var_PD, cov_PD_AL, var_AL),
     x = scale(pub_year, center = 1979), data = Berkey98, RE.lbound = NA)
    
    95% confidence intervals: z statistic approximation (robust=FALSE)
    Coefficients:
     Estimate Std.Error lbound ubound z value Pr(>|z|)
    Intercept1 0.3440001 NA NA NA NA NA
    Intercept2 -0.2918174 0.1060232 -0.4996192 -0.0840157 -2.7524 0.005916 **
    Slope1_1 0.0063540 0.0421617 -0.0762814 0.0889894 0.1507 0.880208
    Slope2_1 -0.0705888 0.1155356 -0.2970343 0.1558568 -0.6110 0.541219
    Tau2_1_1 0.0080405 0.0092425 -0.0100744 0.0261555 0.8700 0.384326
    Tau2_2_1 0.0093413 0.0096829 -0.0096368 0.0283194 0.9647 0.334682
    Tau2_2_2 0.0250135 0.0166350 -0.0075904 0.0576174 1.5037 0.132666
    ---
    Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
    
    Q statistic on the homogeneity of effect sizes: 128.2267
    Degrees of freedom of the Q statistic: 8
    P value of the Q statistic: 0
    
    Explained variances (R2):
     y1 y2
    Tau2 (no predictor) 0.0070020 0.0261
    Tau2 (with predictors) 0.0080405 0.0250
    R2 0.0000000 0.0433
    
    Number of studies (or clusters): 5
    Number of observed statistics: 10
    Number of estimated parameters: 7
    Degrees of freedom: 3
    -2 log likelihood: -12.00859
    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 with equality constraint on the regression coefficients
    > summary( meta(y=cbind(PD, AL), v=cbind(var_PD, cov_PD_AL, var_AL),
    + x=scale(pub_year, center=1979), data=Berkey98,
    + coef.constraints=matrix(c("0.3*Eq_slope", "0.3*Eq_slope"),
    + nrow=2)) )
    
    Call:
    meta(y = cbind(PD, AL), v = cbind(var_PD, cov_PD_AL, var_AL),
     x = scale(pub_year, center = 1979), data = Berkey98, coef.constraints = matrix(c("0.3*Eq_slope",
     "0.3*Eq_slope"), nrow = 2))
    
    95% confidence intervals: z statistic approximation (robust=FALSE)
    Coefficients:
     Estimate Std.Error lbound ubound z value Pr(>|z|)
    Intercept1 3.4376e-01 2.1942e-05 3.4372e-01 3.4380e-01 15666.9410 <2e-16
    Intercept2 -3.3900e-01 7.5489e-05 -3.3915e-01 -3.3885e-01 -4490.7161 <2e-16
    Eq_slope 1.6748e-03 2.5127e-02 -4.7573e-02 5.0923e-02 0.0667 0.9469
    Tau2_1_1 7.0474e-03 7.6032e-03 -7.8545e-03 2.1949e-02 0.9269 0.3540
    Tau2_2_1 9.5165e-03 8.3911e-03 -6.9297e-03 2.5963e-02 1.1341 0.2567
    Tau2_2_2 2.6198e-02 1.5956e-02 -5.0748e-03 5.7471e-02 1.6419 0.1006
    
    Intercept1 ***
    Intercept2 ***
    Eq_slope
    Tau2_1_1
    Tau2_2_1
    Tau2_2_2
    ---
    Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
    
    Q statistic on the homogeneity of effect sizes: 128.2267
    Degrees of freedom of the Q statistic: 8
    P value of the Q statistic: 0
    
    Explained variances (R2):
     y1 y2
    Tau2 (no predictor) 0.0070020 0.0261
    Tau2 (with predictors) 0.0070474 0.0262
    R2 0.0000000 0.0000
    
    Number of studies (or clusters): 5
    Number of observed statistics: 10
    Number of estimated parameters: 6
    Degrees of freedom: 4
    -2 log likelihood: -11.68158
    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.
    
    >
    > #### REML estimation method
    > ## Multivariate meta-analysis
    > summary( reml(y=cbind(PD, AL), v=cbind(var_PD, cov_PD_AL, var_AL),
    + data=Berkey98,
    + model.name="Multivariate meta analysis with REML") )
    Error: C stack usage 279221396 is too close to the limit
    Error in running the mxModel:
    <simpleError: The job for model 'Multivariate meta analysis with REML' exited abnormally with the error message: User interrupt>
    Error in (function (cond) :
     error in evaluating the argument 'object' in selecting a method for function 'summary': The job for model 'Multivariate meta analysis with REML' exited abnormally with the error message: User interrupt
    Calls: summary -> reml
    Execution halted
Flavor: r-patched-solaris-x86

Version: 1.2.4
Check: tests
Result: ERROR
     Running ‘testthat.R’ [16s/19s]
    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 in running mxModel:
     <simpleError: The job for model 'Meta analysis with FIML' exited abnormally with the error message: Non-conformable matrices in horizontal concatenation (cbind). First argument has 4 rows, and argument #2 has 0 rows.>
     ── 1. Error: metaFIML() works correctly (@test_utilities.R#551) ───────────────
     The job for model 'Meta analysis with FIML' exited abnormally with the error message: Non-conformable matrices in horizontal concatenation (cbind). First argument has 4 rows, and argument #2 has 0 rows.
     Backtrace:
     1. metaSEM::metaFIML(y = r, v = r_v, x = JP_alpha, av = IDV, data = Jaramillo05)
    
     Error: C stack usage 279352468 is too close to the limit
     <simpleError: The job for model 'TSSEM1 Correlation' exited abnormally with the error message: User interrupt>
     ── 2. Error: Handling NA in diagonals in tssem1FEM() correctly (@test_utilities.
     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")
     2. metaSEM::tssem1FEM(...)
    
     ══ testthat results ═══════════════════════════════════════════════════════════
     [ OK: 92 | SKIPPED: 0 | WARNINGS: 1 | FAILED: 2 ]
     1. Error: metaFIML() works correctly (@test_utilities.R#551)
     2. Error: Handling NA in diagonals in tssem1FEM() correctly (@test_utilities.R#644)
    
     Error: testthat unit tests failed
     Execution halted
Flavor: r-patched-solaris-x86