R Under development (unstable) (2023-08-28 r85029 ucrt) -- "Unsuffered Consequences"
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> # This file is part of the standard setup for testthat.
> # It is recommended that you do not modify it.
> #
> # Where should you do additional test configuration?
> # Learn more about the roles of various files in:
> # * https://r-pkgs.org/tests.html
> # * https://testthat.r-lib.org/reference/test_package.html#special-files
> 
> library(testthat)
> library(phantSEM)
> 
> test_check("phantSEM")
This is lavaan 0.6-16
lavaan is FREE software! Please report any bugs.
Here are the phantom covariance matrix parameters (copy and paste and add values/names for step2):

              
phantom_assignment <-( "CovM1M2"= ,
"CovM1X"= ,
"CovM1Y2"= ,
"CovY1M1"= ,
"CovY1M2"= ,
"CovY1X"= ,
"CovY1Y2"= ,
"VarM1"= ,
"VarY1" = )
 Choose the names of the phantom covariances that you want to fix to single values and put in a vector. These will be used for the fixed_names argument in the SA_step2 function.  The phantom covariance parameters that you want to vary should be put in a list and used as the test_names argument. 
Here are the observed covariance matrix parameters:
[1] "CovM2Y2" "CovXM2"  "CovXY2" 
Choose which values you want to use for your fixed parameters and put their names in a vector (fixed_values). Make sure the order is the same for both vectors.
Here are the phantom covariance matrix parameters (copy and paste and add values/names for step2):

              
phantom_assignment <-( "CovM1M2"= ,
"CovM1X"= ,
"CovM1Y2"= ,
"CovY1M1"= ,
"CovY1M2"= ,
"CovY1X"= ,
"CovY1Y2"= ,
"VarM1"= ,
"VarY1" = )
 Choose the names of the phantom covariances that you want to fix to single values and put in a vector. These will be used for the fixed_names argument in the SA_step2 function.  The phantom covariance parameters that you want to vary should be put in a list and used as the test_names argument. 
Here are the observed covariance matrix parameters:
[1] "CovM2Y2" "CovXM2"  "CovXY2" 
Choose which values you want to use for your fixed parameters and put their names in a vector (fixed_values). Make sure the order is the same for both vectors.
Here are the phantom covariance matrix parameters (copy and paste and add values/names for step2):

              
phantom_assignment <-( "CovM1M2"= ,
"CovM1X"= ,
"CovM1Y2"= ,
"CovY1M1"= ,
"CovY1M2"= ,
"CovY1X"= ,
"CovY1Y2"= ,
"VarM1"= ,
"VarY1" = )
 Choose the names of the phantom covariances that you want to fix to single values and put in a vector. These will be used for the fixed_names argument in the SA_step2 function.  The phantom covariance parameters that you want to vary should be put in a list and used as the test_names argument. 
Here are the observed covariance matrix parameters:
[1] "CovM2Y2" "CovXM2"  "CovXY2" 
Choose which values you want to use for your fixed parameters and put their names in a vector (fixed_values). Make sure the order is the same for both vectors.
Here are the phantom covariance matrix parameters (copy and paste and add values/names for step2):

              
phantom_assignment <-( "CovM1M2"= ,
"CovM1X"= ,
"CovM1Y2"= ,
"CovY1M1"= ,
"CovY1M2"= ,
"CovY1X"= ,
"CovY1Y2"= ,
"VarM1"= ,
"VarY1" = )
 Choose the names of the phantom covariances that you want to fix to single values and put in a vector. These will be used for the fixed_names argument in the SA_step2 function.  The phantom covariance parameters that you want to vary should be put in a list and used as the test_names argument. 
Here are the observed covariance matrix parameters:
[1] "CovM2Y2" "CovXM2"  "CovXY2" 
Choose which values you want to use for your fixed parameters and put their names in a vector (fixed_values). Make sure the order is the same for both vectors.
Here are the phantom covariance matrix parameters (copy and paste and add values/names for step2):

              
phantom_assignment <-( "CovM1M2"= ,
"CovM1X"= ,
"CovM1Y2"= ,
"CovY1M1"= ,
"CovY1M2"= ,
"CovY1X"= ,
"CovY1Y2"= ,
"VarM1"= ,
"VarY1" = )
 Choose the names of the phantom covariances that you want to fix to single values and put in a vector. These will be used for the fixed_names argument in the SA_step2 function.  The phantom covariance parameters that you want to vary should be put in a list and used as the test_names argument. 
Here are the observed covariance matrix parameters:
[1] "CovM2Y2" "CovXM2"  "CovXY2" 
Choose which values you want to use for your fixed parameters and put their names in a vector (fixed_values). Make sure the order is the same for both vectors.
Here are the phantom covariance matrix parameters (copy and paste and add values/names for step2):

              
phantom_assignment <-( "CovM1M2"= ,
"CovM1X"= ,
"CovM1Y2"= ,
"CovY1M1"= ,
"CovY1M2"= ,
"CovY1X"= ,
"CovY1Y2"= ,
"VarM1"= ,
"VarY1" = )
 Choose the names of the phantom covariances that you want to fix to single values and put in a vector. These will be used for the fixed_names argument in the SA_step2 function.  The phantom covariance parameters that you want to vary should be put in a list and used as the test_names argument. 
Here are the observed covariance matrix parameters:
[1] "CovM2Y2" "CovXM2"  "CovXY2" 
Choose which values you want to use for your fixed parameters and put their names in a vector (fixed_values). Make sure the order is the same for both vectors.
Here are the phantom covariance matrix parameters (copy and paste and add values/names for step2):

              
phantom_assignment <-( "CovM1M2"= ,
"CovM1X"= ,
"CovM1Y2"= ,
"CovY1M1"= ,
"CovY1M2"= ,
"CovY1X"= ,
"CovY1Y2"= ,
"VarM1"= ,
"VarY1" = )
 Choose the names of the phantom covariances that you want to fix to single values and put in a vector. These will be used for the fixed_names argument in the SA_step2 function.  The phantom covariance parameters that you want to vary should be put in a list and used as the test_names argument. 
Here are the observed covariance matrix parameters:
[1] "CovM2Y2" "CovXM2"  "CovXY2" 
Choose which values you want to use for your fixed parameters and put their names in a vector (fixed_values). Make sure the order is the same for both vectors.
Here are the phantom covariance matrix parameters (copy and paste and add values/names for step2):

              
phantom_assignment <-( "CovM1M2"= ,
"CovM1X"= ,
"CovM1Y2"= ,
"CovY1M1"= ,
"CovY1M2"= ,
"CovY1X"= ,
"CovY1Y2"= ,
"VarM1"= ,
"VarY1" = )
 Choose the names of the phantom covariances that you want to fix to single values and put in a vector. These will be used for the fixed_names argument in the SA_step2 function.  The phantom covariance parameters that you want to vary should be put in a list and used as the test_names argument. 
Here are the observed covariance matrix parameters:
[1] "CovM2Y2" "CovXM2"  "CovXY2" 
Choose which values you want to use for your fixed parameters and put their names in a vector (fixed_values). Make sure the order is the same for both vectors.
Here are the phantom covariance matrix parameters (copy and paste and add values/names for step2):

              
phantom_assignment <-( "CovM1M2"= ,
"CovM1X"= ,
"CovM1Y2"= ,
"CovY1M1"= ,
"CovY1M2"= ,
"CovY1X"= ,
"CovY1Y2"= ,
"VarM1"= ,
"VarY1" = )
 Choose the names of the phantom covariances that you want to fix to single values and put in a vector. These will be used for the fixed_names argument in the SA_step2 function.  The phantom covariance parameters that you want to vary should be put in a list and used as the test_names argument. 
Here are the observed covariance matrix parameters:
[1] "CovM2Y2" "CovXM2"  "CovXY2" 
Choose which values you want to use for your fixed parameters and put their names in a vector (fixed_values). Make sure the order is the same for both vectors.
Here are the phantom covariance matrix parameters (copy and paste and add values/names for step2):

              
phantom_assignment <-( "CovM1M2"= ,
"CovM1X"= ,
"CovM1Y2"= ,
"CovY1M1"= ,
"CovY1M2"= ,
"CovY1X"= ,
"CovY1Y2"= ,
"VarM1"= ,
"VarY1" = )
 Choose the names of the phantom covariances that you want to fix to single values and put in a vector. These will be used for the fixed_names argument in the SA_step2 function.  The phantom covariance parameters that you want to vary should be put in a list and used as the test_names argument. 
Here are the observed covariance matrix parameters:
[1] "CovM2Y2" "CovXM2"  "CovXY2" 
Choose which values you want to use for your fixed parameters and put their names in a vector (fixed_values). Make sure the order is the same for both vectors.
[1] 1
[1] 2
[1] 3
[1] TRUE
[1] TRUE
[1] TRUE
[1] 0
[1] TRUE
[1] 0
[1] TRUE
[1] 1
[1] TRUE
[1] 1
Here are the phantom covariance matrix parameters (copy and paste and add values/names for step2):

              
phantom_assignment <-( "CovM1M2"= ,
"CovM1X"= ,
"CovM1Y2"= ,
"CovY1M1"= ,
"CovY1M2"= ,
"CovY1X"= ,
"CovY1Y2"= ,
"VarM1"= ,
"VarY1" = )
 Choose the names of the phantom covariances that you want to fix to single values and put in a vector. These will be used for the fixed_names argument in the SA_step2 function.  The phantom covariance parameters that you want to vary should be put in a list and used as the test_names argument. 
Here are the observed covariance matrix parameters:
[1] "CovM2Y2" "CovXM2"  "CovXY2" 
Choose which values you want to use for your fixed parameters and put their names in a vector (fixed_values). Make sure the order is the same for both vectors.
[1] 1
[1] 2
[1] TRUE
[1] TRUE
[1] 0
[1] TRUE
[1] 0
[1] TRUE
[1] 1
[1] TRUE
[1] 1
Here are the phantom covariance matrix parameters (copy and paste and add values/names for step2):

              
phantom_assignment <-( "CovM1M2"= ,
"CovM1X"= ,
"CovM1Y2"= ,
"CovY1M1"= ,
"CovY1M2"= ,
"CovY1X"= ,
"CovY1Y2"= ,
"VarM1"= ,
"VarY1" = )
 Choose the names of the phantom covariances that you want to fix to single values and put in a vector. These will be used for the fixed_names argument in the SA_step2 function.  The phantom covariance parameters that you want to vary should be put in a list and used as the test_names argument. 
Here are the observed covariance matrix parameters:
[1] "CovM2Y2" "CovXM2"  "CovXY2" 
Choose which values you want to use for your fixed parameters and put their names in a vector (fixed_values). Make sure the order is the same for both vectors.
[1] 1
[1] 2
[1] 3
[1] FALSE
[1] FALSE
Here are the phantom covariance matrix parameters (copy and paste and add values/names for step2):

              
phantom_assignment <-( "CovM1M2"= ,
"CovM1X"= ,
"CovM1Y2"= ,
"CovY1M1"= ,
"CovY1M2"= ,
"CovY1X"= ,
"CovY1Y2"= ,
"VarM1"= ,
"VarY1" = )
 Choose the names of the phantom covariances that you want to fix to single values and put in a vector. These will be used for the fixed_names argument in the SA_step2 function.  The phantom covariance parameters that you want to vary should be put in a list and used as the test_names argument. 
Here are the observed covariance matrix parameters:
[1] "CovM2Y2" "CovXM2"  "CovXY2" 
Choose which values you want to use for your fixed parameters and put their names in a vector (fixed_values). Make sure the order is the same for both vectors.
[1] 1
[1] 2
[1] TRUE
[1] TRUE
[1] 1
[1] TRUE
[1] 1
[1] 1
[1] 2
[1] TRUE
[1] TRUE
[1] 1
[1] TRUE
[1] 1
[1] 1
[1] 2
[1] TRUE
[1] TRUE
[1] 1
[1] TRUE
[1] 1
[1] 1
[1] 2
[1] TRUE
[1] TRUE
[1] 1
[1] TRUE
[1] 1
Here are the phantom covariance matrix parameters (copy and paste and add values/names for step2):

              
phantom_assignment <-( "CovM1M2"= ,
"CovM1X"= ,
"CovM1Y2"= ,
"CovY1M1"= ,
"CovY1M2"= ,
"CovY1X"= ,
"CovY1Y2"= ,
"VarM1"= ,
"VarY1" = )
 Choose the names of the phantom covariances that you want to fix to single values and put in a vector. These will be used for the fixed_names argument in the SA_step2 function.  The phantom covariance parameters that you want to vary should be put in a list and used as the test_names argument. 
Here are the observed covariance matrix parameters:
[1] "CovM2Y2" "CovXM2"  "CovXY2" 
Choose which values you want to use for your fixed parameters and put their names in a vector (fixed_values). Make sure the order is the same for both vectors.
[1] 1
[1] FALSE
logical(0)
Here are the phantom covariance matrix parameters (copy and paste and add values/names for step2):

              
phantom_assignment <-( "CovM1M2"= ,
"CovM1X"= ,
"CovM1Y2"= ,
"CovY1M1"= ,
"CovY1M2"= ,
"CovY1X"= ,
"CovY1Y2"= ,
"VarM1"= ,
"VarY1" = )
 Choose the names of the phantom covariances that you want to fix to single values and put in a vector. These will be used for the fixed_names argument in the SA_step2 function.  The phantom covariance parameters that you want to vary should be put in a list and used as the test_names argument. 
Here are the observed covariance matrix parameters:
[1] "CovM2Y2" "CovXM2"  "CovXY2" 
Choose which values you want to use for your fixed parameters and put their names in a vector (fixed_values). Make sure the order is the same for both vectors.
[1] 1
[1] FALSE
logical(0)
[1] TRUE
[1] 0.4
[1] TRUE
[1] 0
[1] TRUE
[1] 0.5
[1] TRUE
[1] 0.3
[1] TRUE
[1] 0.1
[1] TRUE
[1] 0
[1] TRUE
[1] 1
[1] TRUE
[1] 1
Here are the phantom covariance matrix parameters (copy and paste and add values/names for step2):

              
phantom_assignment <-( "CovM1M2"= ,
"CovM1X"= ,
"CovM1Y2"= ,
"CovY1M1"= ,
"CovY1M2"= ,
"CovY1X"= ,
"CovY1Y2"= ,
"VarM1"= ,
"VarY1" = )
 Choose the names of the phantom covariances that you want to fix to single values and put in a vector. These will be used for the fixed_names argument in the SA_step2 function.  The phantom covariance parameters that you want to vary should be put in a list and used as the test_names argument. 
Here are the observed covariance matrix parameters:
[1] "CovM2Y2" "CovXM2"  "CovXY2" 
Choose which values you want to use for your fixed parameters and put their names in a vector (fixed_values). Make sure the order is the same for both vectors.
[1] 1
[1] FALSE
logical(0)
[ FAIL 0 | WARN 0 | SKIP 0 | PASS 17 ]
> 
> proc.time()
   user  system elapsed 
   1.65    0.29    1.93