CRAN Package Check Results for Package metaSEM

Last updated on 2019-07-16 07:50:53 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 1.2.2 14.50 125.82 140.32 OK
r-devel-linux-x86_64-debian-gcc 1.2.2 13.20 95.27 108.47 OK
r-devel-linux-x86_64-fedora-clang 1.2.2 165.16 OK
r-devel-linux-x86_64-fedora-gcc 1.2.2 157.62 OK
r-devel-windows-ix86+x86_64 1.2.2 39.00 120.00 159.00 OK
r-patched-linux-x86_64 1.2.2 13.36 119.42 132.78 OK
r-patched-solaris-x86 1.2.2 224.10 ERROR
r-release-linux-x86_64 1.2.2 14.79 117.79 132.58 OK
r-release-windows-ix86+x86_64 1.2.2 26.00 176.00 202.00 OK
r-release-osx-x86_64 1.2.2 OK
r-oldrel-windows-ix86+x86_64 1.2.2 28.00 168.00 196.00 OK
r-oldrel-osx-x86_64 1.2.2 OK

Check Details

Version: 1.2.2
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
    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 -0.0098617 0.0071587 -0.3113 0.7556
    Tau2_1_1 0.0020944 0.0043414 -0.0064145 0.0106033 0.4824 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
    Coefficients:
     Estimate Std.Error lbound ubound z value Pr(>|z|)
    Intercept1 0.10000000 NA NA NA NA NA
    Intercept2 0.10000000 NA NA NA NA NA
    Tau2_1_1 0.10000000 0.00089175 0.09825221 0.10174779 112.14 < 2.2e-16 ***
    Tau2_2_1 0.10000000 0.00032821 0.09935672 0.10064328 304.68 < 2.2e-16 ***
    Tau2_2_2 0.10000000 0.00098492 0.09806959 0.10193041 101.53 < 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) 0.8593
    Intercept2: I2 (Q statistic) 0.9020
    
    Number of studies (or clusters): 13
    Number of observed statistics: 26
    Number of estimated parameters: 5
    Degrees of freedom: 21
    -2 log likelihood: 2493.203
    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