Error: object 'permuteOnce.mgcfa' not found when using `parallelType = "snow"` in `permuteMeasEq()`

[isaactpetersen]

I'm receiving the following error when trying to set parallelType = "snow" in permuteMeasEq():
Error in get(name, envir = envir): object 'permuteOnce.mgcfa' not found

I'm using semTools_0.5-5 on Windows. The call to permuteMeasEq() works fine when I remove the call to parallelType. A reprex (with my session info) is below:

library("lavaan")
#> This is lavaan 0.6-9
#> lavaan is FREE software! Please report any bugs.
library("semTools")
#> 
#> ###############################################################################
#> This is semTools 0.5-5
#> All users of R (or SEM) are invited to submit functions or ideas for functions.
#> ###############################################################################

HS <- lavaan::HolzingerSwineford1939
HS$ageGroup <- ifelse(HS$ageyr < 13, "preteen",
                      ifelse(HS$ageyr > 13, "teen", "thirteen"))

mod.null <- c(paste0("x", 1:9, " ~ c(T", 1:9, ", T", 1:9, ", T", 1:9, ")*1"),
              paste0("x", 1:9, " ~~ c(L", 1:9, ", L", 1:9, ", L", 1:9, ")*x", 1:9))
fit.null <- cfa(mod.null, data = HS, group = "ageGroup")

mod.config <- '
visual  =~ x1 + x2 + x3
textual =~ x4 + x5 + x6
speed   =~ x7 + x8 + x9
'

configuralInvarianceModel <- measEq.syntax(configural.model = mod.config,
                                           data = HS,
                                           ID.fac = "std.lv",
                                           group = "ageGroup")

configuralInvarianceSyntax <- as.character(configuralInvarianceModel)

configuralInvarianceModel_fit <- cfa(configuralInvarianceSyntax,
                                     data = HS,
                                     std.lv = TRUE,
                                     group = "ageGroup",
                                     missing = "ML",
                                     estimator = "MLR")

myAFIs <- c("chisq","cfi","rmsea","mfi","aic")
moreAFIs <- c("gammaHat","adjGammaHat")

# test configural invariance -- this works
set.seed(12345)
out.config <- permuteMeasEq(nPermute = 20,
                            con = configuralInvarianceModel_fit,
                            AFIs = myAFIs,
                            moreAFIs = moreAFIs,
                            iseed = 12345)
#>   |                                                          |                                                  |   0%  |                                                          |===                                               |   5%  |                                                          |=====                                             |  11%  |                                                          |========                                          |  16%  |                                                          |===========                                       |  21%  |                                                          |=============                                     |  26%  |                                                          |================                                  |  32%  |                                                          |==================                                |  37%  |                                                          |=====================                             |  42%  |                                                          |========================                          |  47%  |                                                          |==========================                        |  53%  |                                                          |=============================                     |  58%  |                                                          |================================                  |  63%  |                                                          |==================================                |  68%  |                                                          |=====================================             |  74%  |                                                          |=======================================           |  79%  |                                                          |==========================================        |  84%  |                                                          |=============================================     |  89%  |                                                          |===============================================   |  95%  |                                                          |==================================================| 100%

# test configural invariance -- this throws an error
set.seed(12345)
out.config <- permuteMeasEq(nPermute = 20,
                            con = configuralInvarianceModel_fit,
                            AFIs = myAFIs,
                            moreAFIs = moreAFIs,
                            parallelType = "snow",
                            iseed = 12345)
#> Your RNGkind() was changed from Mersenne-Twister to L'Ecuyer-CMRG, which is required for reproducibility  in parallel jobs.  Your RNGkind() has been returned to Mersenne-Twister but the seed has not been set.  The state of your previous RNG is saved in the slot  named 'oldSeed', if you want to restore it using  the syntax:
#> .Random.seed[-1] <- permuteMeasEqObject@oldSeed[-1]
#> Error in get(name, envir = envir): object 'permuteOnce.mgcfa' not found

sessionInfo()
#> R version 4.1.0 (2021-05-18)
#> Platform: x86_64-w64-mingw32/x64 (64-bit)
#> Running under: Windows 10 x64 (build 19041)
#> 
#> Matrix products: default
#> 
#> Random number generation:
#>  RNG:     L'Ecuyer-CMRG 
#>  Normal:  Inversion 
#>  Sample:  Rejection 
#>  
#> locale:
#> [1] LC_COLLATE=English_United States.1252 
#> [2] LC_CTYPE=English_United States.1252   
#> [3] LC_MONETARY=English_United States.1252
#> [4] LC_NUMERIC=C                          
#> [5] LC_TIME=English_United States.1252    
#> 
#> attached base packages:
#> [1] stats     graphics  grDevices utils     datasets  methods   base     
#> 
#> other attached packages:
#> [1] semTools_0.5-5 lavaan_0.6-9  
#> 
#> loaded via a namespace (and not attached):
#>  [1] pillar_1.6.1         compiler_4.1.0       highr_0.9           
#>  [4] tools_4.1.0          digest_0.6.27        lattice_0.20-44     
#>  [7] evaluate_0.14        lifecycle_1.0.0      tibble_3.1.2        
#> [10] pkgconfig_2.0.3      rlang_0.4.11.9000    Matrix_1.3-4        
#> [13] reprex_2.0.0         cli_3.0.0            parallel_4.1.0      
#> [16] yaml_2.2.1           mvtnorm_1.1-2        pbivnorm_0.6.0      
#> [19] xfun_0.24            fastmap_1.1.0        coda_0.19-4         
#> [22] withr_2.4.2          styler_1.4.1         stringr_1.4.0       
#> [25] knitr_1.33           fs_1.5.0             vctrs_0.3.8         
#> [28] grid_4.1.0           stats4_4.1.0         glue_1.4.2          
#> [31] fansi_0.5.0          survival_3.2-11      rmarkdown_2.9       
#> [34] multcomp_1.4-17      TH.data_1.0-10       purrr_0.3.4         
#> [37] magrittr_2.0.1       codetools_0.2-18     MASS_7.3-54         
#> [40] splines_4.1.0        backports_1.2.1      ellipsis_0.3.2      
#> [43] htmltools_0.5.1.9005 emmeans_1.6.1        mnormt_2.0.2        
#> [46] xtable_1.8-4         sandwich_3.0-1       utf8_1.2.1          
#> [49] stringi_1.6.2        estimability_1.3     tmvnsim_1.0-2       
#> [52] crayon_1.4.1         zoo_1.8-9

^{Created on 2021-07-08 by the reprex package (v2.0.0)}