Error when using multiple imputation and multicore = TRUE: no method found for function 'coef' and signature lavaan.mi

[isaactpetersen]

I receive the following error when using multiple imputation and multicore = TRUE on Windows:

Error in checkForRemoteErrors(val): one node produced an error: no method found for function 'coef' and signature lavaan.mi

Here's a reprex:

library("lavaan")
#> This is lavaan 0.6-12
#> lavaan is FREE software! Please report any bugs.
library("semTools")
#> 
#> ###############################################################################
#> This is semTools 0.5-6
#> All users of R (or SEM) are invited to submit functions or ideas for functions.
#> ###############################################################################
library("simsem")
#> 
#> #################################################################
#> This is simsem 0.5-16
#> simsem is BETA software! Please report any bugs.
#> simsem was first developed at the University of Kansas Center for
#> Research Methods and Data Analysis, under NSF Grant 1053160.
#> #################################################################
#> 
#> Attaching package: 'simsem'
#> The following object is masked from 'package:lavaan':
#> 
#>     inspect

# Specify population model
populationModel <- '
 #Factor loadings
 ind60 =~ .75*x1 + .75*x2 + .75*x3
 dem60 =~ .75*y1 + .75*y2 + .75*y3 + .75*y4
 dem65 =~ .75*y5 + .75*y6 + .75*y7 + .75*y8

 #Specify regression coefficients
 dem60 ~ .4*ind60
 dem65 ~ .2*ind60 + .45*dem60
 
 #Fix latent means to zero
 ind60 ~ 0
 dem60 ~ 0
 dem65 ~ 0
 
 #Fix latent variances to one
 ind60 ~~ 1*ind60
 dem60 ~~ 1*dem60
 dem65 ~~ 1*dem65
 
 #Specify residual variances of manifest variables
 x1 ~~ (1-.75^2)*x1
 x2 ~~ (1-.75^2)*x2
 x3 ~~ (1-.75^2)*x3
 y1 ~~ (1-.75^2)*y1
 y2 ~~ (1-.75^2)*y2
 y3 ~~ (1-.75^2)*y3
 y4 ~~ (1-.75^2)*y4
 y5 ~~ (1-.75^2)*y5
 y6 ~~ (1-.75^2)*y6
 y7 ~~ (1-.75^2)*y7
 y8 ~~ (1-.75^2)*y8
 
 #Specify intercepts of manifest variables
 x1 ~ 0*1
 x2 ~ 0*1
 x3 ~ 0*1
 y1 ~ 0*1
 y2 ~ 0*1
 y3 ~ 0*1
 y4 ~ 0*1
 y5 ~ 0*1
 y6 ~ 0*1
 y7 ~ 0*1
 y8 ~ 0*1
'

populationModelFit <- lavaan(populationModel, do.fit = FALSE)

# Specify analysis model
analysisModelSyntax <- '
 #Factor loadings
 ind60 =~ NA*x1 + x2 + x3
 dem60 =~ NA*y1 + y2 + y3 + y4
 dem65 =~ NA*y5 + y6 + y7 + y8

 #Regression paths
 dem60 ~ ind60
 dem65 ~ ind60 + dem60
 
 #Fix latent means to zero
 ind60 ~ 0
 dem60 ~ 0
 dem65 ~ 0
 
 #Fix latent variances to one
 ind60 ~~ 1*ind60
 dem60 ~~ 1*dem60
 dem65 ~~ 1*dem65
 
 #Estimate residual variances of manifest variables
 x1 ~~ x1
 x2 ~~ x2
 x3 ~~ x3
 y1 ~~ y1
 y2 ~~ y2
 y3 ~~ y3
 y4 ~~ y4
 y5 ~~ y5
 y6 ~~ y6
 y7 ~~ y7
 y8 ~~ y8
 
 #Free intercepts of manifest variables
 x1 ~ intx1*1
 x2 ~ intx2*1
 x3 ~ intx3*1
 y1 ~ inty1*1
 y2 ~ inty2*1
 y3 ~ inty3*1
 y4 ~ inty4*1
 y5 ~ inty5*1
 y6 ~ inty6*1
 y7 ~ inty7*1
 y8 ~ inty8*1
'

numberOfIndicators <- length(fitted(populationModelFit)$mean)

indicatorDistributions <- bindDist(p = numberOfIndicators,
                                   skewness = rep(2.5, 11),
                                   kurtosis = rep(5, 11))

percentMissingByVariable <- '
  x1 ~ p(0.10)
  x2 ~ p(0.10)
  x3 ~ p(0.10)
  y1 ~ p(0.10)
  y2 ~ p(0.10)
  y3 ~ p(0.10)
  y4 ~ p(0.10)
  y5 ~ p(0.10)
  y6 ~ p(0.10)
  y7 ~ p(0.10)
  y8 ~ p(0.10)
'

missingnessModelMI <- miss(logit = percentMissingByVariable, m = 5)

output <- simsem::sim(n = 100,
                      model = analysisModelSyntax,
                      generate = populationModel,
                      miss = missingnessModelMI,
                      seed = 52242,
                      multicore = TRUE)
#> Progress tracker is not available when 'multicore' is TRUE.
#> Error in checkForRemoteErrors(val): one node produced an error: no method found for function 'coef' and signature lavaan.mi

sessionInfo()
#> R version 4.2.0 (2022-04-22 ucrt)
#> Platform: x86_64-w64-mingw32/x64 (64-bit)
#> Running under: Windows 10 x64 (build 19044)
#> 
#> Matrix products: default
#> 
#> Random number generation:
#>  RNG:     L'Ecuyer-CMRG 
#>  Normal:  Inversion 
#>  Sample:  Rejection 
#>  
#> locale:
#> [1] LC_COLLATE=English_United States.utf8 
#> [2] LC_CTYPE=English_United States.utf8   
#> [3] LC_MONETARY=English_United States.utf8
#> [4] LC_NUMERIC=C                          
#> [5] LC_TIME=English_United States.utf8    
#> 
#> attached base packages:
#> [1] stats     graphics  grDevices utils     datasets  methods   base     
#> 
#> other attached packages:
#> [1] simsem_0.5-16  semTools_0.5-6 lavaan_0.6-12 
#> 
#> loaded via a namespace (and not attached):
#>  [1] styler_1.7.0      zoo_1.8-10        xfun_0.31         purrr_0.3.4      
#>  [5] splines_4.2.0     lattice_0.20-45   vctrs_0.4.1       snow_0.4-4       
#>  [9] htmltools_0.5.2   stats4_4.2.0      yaml_2.3.5        utf8_1.2.2       
#> [13] survival_3.3-1    rlang_1.0.3       R.oo_1.25.0       pillar_1.7.0     
#> [17] glue_1.6.2        withr_2.5.0       R.utils_2.12.0    emmeans_1.7.5    
#> [21] multcomp_1.4-19   R.cache_0.15.0    lifecycle_1.0.1   stringr_1.4.0    
#> [25] R.methodsS3_1.8.2 mvtnorm_1.1-3     codetools_0.2-18  coda_0.19-4      
#> [29] evaluate_0.15     knitr_1.39        fastmap_1.1.0     parallel_4.2.0   
#> [33] fansi_1.0.3       highr_0.9         TH.data_1.1-1     xtable_1.8-4     
#> [37] fs_1.5.2          mnormt_2.1.0      digest_0.6.29     stringi_1.7.6    
#> [41] grid_4.2.0        cli_3.3.0         tools_4.2.0       sandwich_3.0-2   
#> [45] magrittr_2.0.3    tibble_3.1.7      crayon_1.5.1      pbivnorm_0.6.0   
#> [49] pkgconfig_2.0.3   ellipsis_0.3.2    MASS_7.3-57       Matrix_1.4-1     
#> [53] estimability_1.4  reprex_2.0.1      rmarkdown_2.14    rstudioapi_0.13  
#> [57] compiler_4.2.0

^{Created on 2022-07-07 by the reprex package (v2.0.1)}