Error: package or namespace load failed for ‘lavaan’

SORENA · February 4, 2020, 4:46pm

Hello, I tried to install lavaan package (latent variable analysis), but I received an error that I need mnormt. So, this time, I uninstalled RStudio and even R, and reinstalled again and installed the packages in order (mnormt, then lavaan). Unfortunately, I received the same error:

Error: package or namespace load failed for ‘lavaan’ in loadNamespace(j <- i[[1L]], c(lib.loc, .libPaths()), versionCheck = vI[[j]]):
 there is no package called ‘mnormt’

This is getting really frustrating. What I need here is the HolzingerSwineford1939 dataset which I cannot access. When I run the code data(HolzingerSwineford1939), I face this error:

Warning message:
In data(HolzingerSwineford1939) :
  data set ‘HolzingerSwineford1939’ not found```

Any help is appreciated.

nirgrahamuk · February 4, 2020, 4:51pm

If I understood correctly, and you'v installed lavaan. and just want the dataset
try

lavaan::HolzingerSwineford1939

SORENA · February 4, 2020, 5:11pm

That didn't help. I received the first error I posted.

nirgrahamuk · February 4, 2020, 5:13pm

dput(lavaan::HolzingerSwineford1939)

structure(list(id = c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 11L, 
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12L, 14L, 13L, 13L, 13L, 14L, 14L, 14L, 13L), agemo = c(1L, 7L, 
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5L, 3L, 1L, 4L, 6L, 11L, 11L, 3L, 0L, 3L, 5L, 10L, 3L, 2L, 5L
), school = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
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1L, 1L, 1L), .Label = c("Grant-White", "Pasteur"), class = "factor"), 
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    5.5, 4, 3.8333333, 5.1666667, 4.3333333, 4.1666667, 5, 4.3333333, 
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    4.5, 6.8333333, 5.5, 6.3333333, 4.1666667, 5.6666667, 6.3333333, 
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    3.5, 4.6666667, 4.8333333, 5, 7.5, 5.3333333, 6.1666667, 
    5.3333333, 4.3333333, 4.8333333, 6, 5, 4.1666667, 5.6666667, 
    5, 3.5, 7.3333333, 6.1666667, 4.8333333, 5.6666667, 5.5, 
    5.1666667, 3.1666667, 5, 7.1666667, 7.3333333, 2, 3.8333333, 
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    5.6666667, 4.8333333, 2.6666667, 5, 6, 4.6666667, 5, 3.3333333, 
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    5.8333333, 5.8333333, 3.8333333, 5.1666667, 8.5, 5.5, 3.5, 
    6.1666667, 6.1666667, 6.1666667, 6.5, 6.5, 3, 4.6666667, 
    4.8333333, 4.1666667, 4.8333333, 5.3333333, 5, 5.8333333, 
    2.6666667, 6.3333333, 4.3333333, 5.5, 4.6666667, 4.5, 4.3333333, 
    5, 3.6666667, 5.3333333, 5.1666667, 5.3333333, 6.6666667, 
    3.5, 5.1666667, 4, 6.8333333, 5, 5.8333333, 5.6666667, 4.1666667, 
    4, 6, 3.3333333, 4.6666667, 5.6666667, 5.6666667, 5.8333333, 
    6.1666667, 4, 3, 4.6666667, 4.3333333, 4.3333333), x2 = c(7.75, 
    5.25, 5.25, 7.75, 4.75, 5, 6, 6.25, 5.75, 5.25, 5.75, 6, 
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    7, 4.5, 4, 7.75, 5.75, 5, 5.25, 5.25, 5.5, 5.5, 8.5, 4.75, 
    5.5, 6.25, 5.75, 6, 7.5, 4.75, 6, 5.25, 4.75, 5.25, 6.5, 
    5.75, 5.75, 6, 6.75, 5, 5.75, 6, 9.25, 5.75, 5, 5, 4.5, 9.25, 
    4.5, 6, 5.25, 5.25, 7, 5.75, 5.5, 5.25, 6, 8, 8.25, 6.5, 
    5.25, 6.25, 7, 6, 7.25, 5, 6.5, 6.25, 4.75, 3.5, 5.5, 5.75, 
    4.75, 7.5, 3.75, 6.25, 3.75, 6.5, 7.75, 5.25, 9, 6.5, 6.5, 
    6.75, 5.5, 4.25, 9.25, 5.25, 6.25, 6.5, 7.5, 5.75, 5.75, 
    5.25, 7.25, 4.75, 6, 5.5, 7, 5.25, 6.75, 8.75, 7, 7, 7.5, 
    4.5, 8, 5.5, 6.25, 5.25, 8, 7.5, 5.25, 6.25, 6.75, 5, 3.75, 
    7.5, 9, 6.75, 5.5, 5.5, 6, 5.75, 4.75, 5.5, 7.25, 4.75, 5, 
    6, 6.75, 5.75, 4.75, 5.5, 6, 5.75, 6.25, 6.25, 8.25, 6.25, 
    6.25, 6.25, 6.5, 5.25, 7.75, 5.25, 7, 7.75, 7.75, 5.75, 5.5, 
    7, 4, 6.5, 6, 6.75, 6.75, 5.5, 5.25, 5.75, 5.75, 8.5, 7.5, 
    5, 4.75, 5.5, 5, 6.25, 7, 5.5, 5, 7.5, 5.25, 5.25, 5.5, 5, 
    6, 6.5, 6, 5, 4.75, 6.5, 7.5, 5.75, 6.25, 6.75, 7.75, 6.5, 
    6, 8.5, 5, 8.5, 5.25, 5.25, 6.25, 6.75, 5, 5, 9.25, 3.75, 
    5.25, 7.5, 6, 5.5, 5.25, 7, 5.75, 5.25, 2.25, 5.5, 5.5, 6.75, 
    5.5, 6.5, 6.25, 7.25, 7.25, 6.25, 7, 6.5, 6, 9.25, 8.5, 6, 
    6.25, 5.25, 7, 6.5, 7, 6.5, 8, 5, 6.5, 6.5, 8.5, 4, 7, 5.75, 
    5, 8.25, 5.25, 5.25, 7, 8.5, 7.5, 6.25, 7, 6.75, 5.5, 7.25, 
    8, 5.75, 6, 5.75, 6.25, 5.25, 5, 6.25, 6, 6.25, 5.75, 5, 
    6.75, 5.5, 6.25, 6.5, 4.75, 6, 5.5, 5.25, 7, 6.5, 7, 6, 5.5, 
    6.75, 6), x3 = c(0.375, 2.125, 1.875, 3, 0.875, 2.25, 1, 
    1.875, 1.5, 0.75, 2, 2.875, 4.125, 1.75, 3.625, 2.375, 1.5, 
    2.25, 4, 3, 2, 4.125, 1.875, 1.625, 1.25, 3.375, 4.5, 2.125, 
    4.25, 0.75, 1.375, 0.25, 1.75, 2.375, 1.5, 0.5, 3.5, 2.25, 
    3.875, 2.5, 1.625, 1.25, 1, 1.875, 2.75, 4.5, 4, 1.375, 2.75, 
    1.125, 3.75, 2.125, 3.25, 1.75, 4.125, 2.125, 3.25, 3.875, 
    2, 1.75, 3.375, 3.625, 1.375, 1.25, 3.625, 2.5, 4, 3.625, 
    0.875, 0.75, 0.75, 3.375, 2.625, 3.25, 2.125, 2.375, 2.125, 
    1.375, 4.125, 2.5, 1.75, 4.25, 2.25, 1.75, 0.625, 2.5, 2.875, 
    2.75, 3.25, 2.25, 2.625, 3.375, 2.125, 0.875, 0.875, 4.25, 
    0.5, 2.125, 1.375, 2.75, 4.375, 1.875, 1.875, 1.625, 4.375, 
    3.125, 0.75, 3.75, 1.625, 2.25, 4.375, 2.625, 4.25, 1.75, 
    3.875, 1, 2.5, 4, 3.375, 1.625, 1.5, 2.375, 4.25, 4.125, 
    4.125, 3.125, 1, 1.125, 3.25, 1.625, 4.375, 3.5, 1.75, 2.25, 
    2.625, 3.625, 4.5, 2.75, 4.5, 2.5, 1.5, 4.5, 3.875, 4, 0.625, 
    1.875, 1.25, 1.625, 2.625, 4.375, 4.25, 2.625, 2.375, 2.375, 
    1.125, 1.25, 0.5, 2.125, 2.75, 1.125, 1.25, 2.5, 4.5, 1.125, 
    1.375, 0.75, 0.75, 1, 1.5, 0.75, 3, 2.25, 3.75, 2.5, 2.5, 
    2.75, 1.75, 3.25, 2.375, 3.375, 2, 1.875, 0.625, 0.5, 1.375, 
    0.375, 1.625, 1.625, 1, 1, 1.75, 1.625, 1.25, 0.625, 1, 2.125, 
    1.125, 1.125, 1, 1.75, 3.125, 1.25, 1, 2.75, 1.625, 3.125, 
    1.875, 0.625, 3.25, 1.875, 2, 2.375, 1.25, 2.125, 0.5, 2.375, 
    2.25, 2.25, 3.75, 1.625, 2.25, 1.125, 3.625, 0.875, 1.375, 
    4.125, 2, 1.5, 1.875, 4.125, 0.75, 0.875, 1.75, 4, 1, 1.875, 
    1.75, 0.875, 4.25, 2, 4.375, 3.5, 1.625, 3.625, 0.75, 3.5, 
    2.75, 1.875, 3.125, 0.375, 3.125, 4.25, 2.25, 2.125, 1.375, 
    2.625, 3.625, 3, 4.125, 0.5, 2.25, 1.125, 1.375, 1.375, 1.875, 
    2.625, 2.375, 4, 4.125, 0.875, 1.5, 4, 2, 1.25, 3.25, 1, 
    1, 1.625, 2.125, 1.875, 1.375, 3.25, 2, 1.875, 1.25, 2, 2.125, 
    1.625, 0.75, 2.125, 0.875, 1.125, 1.625, 2.375, 1.25, 3, 
    1.375, 1.625, 1.875, 0.5, 3.375), x4 = c(2.3333333, 1.6666667, 
    1, 2.6666667, 2.6666667, 1, 3.3333333, 3.6666667, 2.6666667, 
    2.6666667, 2, 2.6666667, 2.6666667, 4.6666667, 5, 2.6666667, 
    2, 2, 4.3333333, 3.6666667, 1.6666667, 2, 3.3333333, 2.6666667, 
    2.3333333, 1.6666667, 2.6666667, 1.6666667, 2, 2.6666667, 
    2, 1.6666667, 2.6666667, 3.3333333, 1.3333333, 1.6666667, 
    2.6666667, 3, 4, 3, 2.6666667, 1.6666667, 1.6666667, 2, 4.6666667, 
    3, 0.66666667, 2.6666667, 2, 3.6666667, 1.6666667, 2.3333333, 
    0.66666667, 3.3333333, 2, 2.6666667, 1.6666667, 2.6666667, 
    1, 1.3333333, 4, 2.6666667, 1.6666667, 3.3333333, 2.6666667, 
    3.6666667, 3, 2.6666667, 3, 4.3333333, 2, 1.3333333, 1.6666667, 
    3.3333333, 3, 1.6666667, 4, 0, 4, 1, 1.6666667, 3, 0.33333333, 
    2.3333333, 1, 3.3333333, 2.6666667, 4, 1.3333333, 3.6666667, 
    2.6666667, 2, 1, 2.6666667, 4.6666667, 4, 3.3333333, 5.3333333, 
    1.6666667, 3.6666667, 2.6666667, 3.6666667, 4.3333333, 3.3333333, 
    2.6666667, 2.6666667, 5.3333333, 2.6666667, 5.6666667, 3.3333333, 
    3.6666667, 4.3333333, 5, 4, 1, 3.6666667, 2.6666667, 3, 2.3333333, 
    2.6666667, 2.6666667, 3.3333333, 4, 2.3333333, 3.3333333, 
    4.3333333, 4.3333333, 3.3333333, 3, 2, 4.3333333, 4, 1.3333333, 
    2, 2.6666667, 4, 4.3333333, 3.3333333, 2.3333333, 3.3333333, 
    3.3333333, 2, 3.6666667, 6, 2.6666667, 3.6666667, 4, 0.66666667, 
    5.6666667, 2.6666667, 5, 3, 3, 1.3333333, 3, 3, 3.3333333, 
    2.6666667, 3.6666667, 3, 2.6666667, 3.3333333, 5.6666667, 
    3.3333333, 3.6666667, 3, 3.3333333, 0.33333333, 3.3333333, 
    1.6666667, 4.6666667, 2.3333333, 3.6666667, 3.3333333, 2.6666667, 
    4.3333333, 1.6666667, 4.3333333, 4.6666667, 2.3333333, 2.6666667, 
    3, 4.3333333, 3, 1.3333333, 3, 3, 3, 3, 1.6666667, 2.6666667, 
    3, 3, 0.66666667, 2, 6.3333333, 5, 3, 3, 2.6666667, 4.6666667, 
    3.6666667, 2, 3.6666667, 2.6666667, 3.3333333, 2.3333333, 
    2.3333333, 1.6666667, 2, 4.6666667, 2.3333333, 3, 6, 2.6666667, 
    3.3333333, 6, 2.3333333, 3, 1.6666667, 2, 4.3333333, 3.3333333, 
    5, 3, 2.6666667, 3, 3.3333333, 2.6666667, 5, 2.3333333, 3, 
    5, 2.6666667, 1.6666667, 3, 4.3333333, 5.3333333, 5, 3, 4.3333333, 
    3.3333333, 3.6666667, 3.6666667, 2.6666667, 3.3333333, 3.3333333, 
    4, 3.6666667, 3, 4, 6, 5, 4, 5.3333333, 2.6666667, 2.3333333, 
    5.6666667, 3.3333333, 3.3333333, 3.3333333, 2, 4, 4.3333333, 
    4.6666667, 4, 6, 4.6666667, 4.6666667, 3.3333333, 4.6666667, 
    3.3333333, 2.6666667, 2.6666667, 2.3333333, 1.3333333, 3, 
    4, 1.6666667, 2.6666667, 2.3333333, 5, 2.6666667, 4, 2.6666667, 
    3.3333333, 4.3333333, 2.3333333, 3, 3.3333333, 2.6666667, 
    1.3333333, 3.3333333, 3.3333333, 3, 3, 2.6666667, 2.3333333, 
    3.6666667, 3.6666667, 3.6666667), x5 = c(5.75, 3, 1.75, 4.5, 
    4, 3, 6, 4.25, 5.75, 5, 3.5, 4.5, 4, 4, 5.5, 4.25, 4, 2.5, 
    5.25, 3.75, 2.5, 3.25, 5.75, 3, 3.75, 3.5, 2.25, 3, 3, 3.25, 
    3.5, 3, 5.25, 4.25, 3, 4.75, 4, 3, 5.25, 5.25, 4.25, 4.25, 
    3.75, 3, 5.5, 4.25, 1, 3.25, 2.25, 5.5, 2.25, 4.5, 1.5, 3.5, 
    4.5, 4.5, 3, 5.5, 2.5, 3, 5.5, 5, 2.5, 4.5, 5, 4.5, 3.75, 
    2.75, 2.5, 4, 3, 2.25, 2.75, 5.75, 3.25, 2.25, 4.75, 1.5, 
    3.25, 1.5, 2, 4.75, 2.25, 3.5, 1.5, 5.75, 4, 5, 1.25, 4.5, 
    2.75, 3.75, 2, 3.25, 4.75, 4.25, 5.75, 6.75, 2.75, 4.5, 3.25, 
    3.75, 4.5, 4.5, 5.75, 5.5, 5.75, 2.75, 5.5, 3.5, 4.75, 4.25, 
    3.5, 5.25, 2, 4.75, 4.75, 2.75, 2.25, 3.25, 4.25, 3, 6.5, 
    3.75, 5, 4, 5.5, 5, 6, 2.75, 6.25, 4.25, 2, 3.75, 5, 6.25, 
    5.75, 5.25, 4.5, 5.75, 5.75, 1.5, 5.25, 6.5, 5, 5, 5, 2.5, 
    5.5, 3.75, 5.75, 5.5, 4.25, 2.25, 2.5, 4.75, 4.25, 4.25, 
    4.75, 4.75, 6.25, 5.75, 6.25, 4.5, 5.25, 5.25, 4, 1.75, 2.75, 
    2.5, 5.5, 3, 5.75, 5.75, 4.25, 6, 4.25, 6, 6.5, 3.25, 4.25, 
    5, 4.75, 2.75, 4, 4.75, 4.25, 5, 3.5, 3, 3.75, 5.75, 5.5, 
    1, 4.5, 6, 5, 5.75, 3, 4.5, 4.25, 5.75, 2.5, 4.75, 5.5, 5.5, 
    4, 5, 1.75, 4, 7, 5.25, 5.25, 6, 4.5, 4.25, 6.5, 4, 4, 1.5, 
    3, 4, 4, 4.75, 4, 3.75, 3.5, 4, 4.25, 6, 3.25, 4.75, 6.25, 
    3.25, 2.75, 4.75, 6.25, 6.25, 5.75, 5.75, 5.5, 6.25, 5.75, 
    6.5, 4.25, 4.75, 5, 5, 6, 5.25, 5.75, 6.5, 5.75, 4, 6.25, 
    4.75, 4.75, 6.5, 4.75, 5.25, 6.25, 6, 4.75, 5.75, 5, 6, 6.75, 
    5.5, 5.5, 3.75, 5.25, 4.75, 4.75, 4.75, 3.75, 3.25, 4.75, 
    4.75, 2.75, 4.5, 4.75, 6, 4.5, 5.25, 3.5, 4, 6.25, 4, 4.75, 
    4.75, 5, 3, 4.25, 4.5, 3.25, 4.25, 4.25, 4, 5.75, 4.5, 5.75
    ), x6 = c(1.2857143, 1.2857143, 0.42857143, 2.4285714, 2.5714286, 
    0.85714286, 2.8571429, 1.2857143, 2.7142857, 2.5714286, 1.5714286, 
    2.7142857, 2.2857143, 1.5714286, 3, 0.71428571, 1.2857143, 
    1.7142857, 3.7142857, 2.5714286, 0.57142857, 2.1428571, 3.1428571, 
    1, 1.2857143, 1.4285714, 0.71428571, 1.1428571, 2, 1.8571429, 
    1.8571429, 1, 2, 1.8571429, 0.85714286, 1.4285714, 2, 1.7142857, 
    3.2857143, 3.1428571, 2.1428571, 1.5714286, 0.57142857, 1.4285714, 
    2, 1.2857143, 1, 1.2857143, 1, 2.1428571, 0.14285714, 1.4285714, 
    0.14285714, 2.1428571, 2.1428571, 1.4285714, 1.7142857, 2.4285714, 
    1.2857143, 1, 2.5714286, 2.1428571, 0.71428571, 2.4285714, 
    1.4285714, 3, 1, 1.8571429, 1.5714286, 2.7142857, 1, 1.1428571, 
    1.5714286, 2.7142857, 0.71428571, 1, 2.2857143, 1.1428571, 
    1.8571429, 1.8571429, 1.5714286, 2.4285714, 0.57142857, 0.71428571, 
    1, 3.7142857, 0.85714286, 2.1428571, 0.57142857, 1.7142857, 
    1.8571429, 0.42857143, 1.5714286, 1.1428571, 2.1428571, 2.4285714, 
    2.8571429, 2.7142857, 1.4285714, 3.2857143, 1, 1.7142857, 
    1.8571429, 2.8571429, 5, 2.1428571, 3.1428571, 2, 4, 1.4285714, 
    3, 1.5714286, 1.8571429, 1.8571429, 0.85714286, 1.8571429, 
    2.7142857, 1, 1.1428571, 2, 1.2857143, 2, 3.5714286, 1.5714286, 
    2.8571429, 1.1428571, 3, 2.2857143, 2.4285714, 0.57142857, 
    3.1428571, 2.2857143, 0.57142857, 1.8571429, 2.4285714, 2.5714286, 
    2.8571429, 2.1428571, 2.5714286, 3, 2.2857143, 0.42857143, 
    4.7142857, 6.1428571, 0.85714286, 3, 2.5714286, 1.4285714, 
    4.1428571, 1, 4.8571429, 2.1428571, 2.4285714, 1.1428571, 
    1.4285714, 2.1428571, 1.4285714, 1.4285714, 2.7142857, 1.5714286, 
    3.4285714, 2.5714286, 5.8571429, 1.5714286, 1.1428571, 2.2857143, 
    1.8571429, 1.5714286, 2, 1.4285714, 3.7142857, 1.5714286, 
    2.5714286, 5, 2.8571429, 5.1428571, 1.5714286, 3.5714286, 
    3.4285714, 0.57142857, 1.8571429, 2.4285714, 2.7142857, 1, 
    2.2857143, 2.4285714, 1.8571429, 3, 2.8571429, 0.57142857, 
    1.1428571, 2.1428571, 2.8571429, 0.28571429, 1.8571429, 4.7142857, 
    3.5714286, 3.4285714, 1.1428571, 1.4285714, 1.5714286, 3.2857143, 
    1.4285714, 2.5714286, 2.4285714, 2.5714286, 1.7142857, 1.8571429, 
    0.71428571, 1.8571429, 2.8571429, 2, 2.4285714, 3.8571429, 
    0.85714286, 2.1428571, 4.4285714, 1, 2.2857143, 0.57142857, 
    0.85714286, 2.1428571, 2.2857143, 2.7142857, 2, 1.7142857, 
    1.4285714, 2.4285714, 2.4285714, 5.5714286, 2.7142857, 3.1428571, 
    4.2857143, 1.8571429, 1.5714286, 1.5714286, 3.7142857, 2.1428571, 
    3, 3.2857143, 2.4285714, 3.8571429, 2.5714286, 1.7142857, 
    2.1428571, 2.7142857, 2.7142857, 3.2857143, 2.7142857, 1.7142857, 
    2.1428571, 5.4285714, 4.2857143, 4.7142857, 4.5714286, 2.7142857, 
    2.7142857, 4.2857143, 2.2857143, 2.7142857, 3.2857143, 1.2857143, 
    2.4285714, 3.7142857, 4.1428571, 3.8571429, 4.7142857, 3.4285714, 
    4.1428571, 1.8571429, 2, 2.4285714, 2.1428571, 1.8571429, 
    1.4285714, 2.4285714, 2, 2.1428571, 2.2857143, 1.8571429, 
    1.1428571, 3.2857143, 1.7142857, 2.7142857, 1.7142857, 1.4285714, 
    4.5714286, 1.5714286, 3.2857143, 1.4285714, 0.85714286, 1.5714286, 
    2, 2, 1.5714286, 2.8571429, 1, 1, 4.2857143, 2, 3.1428571
    ), x7 = c(3.3913043, 3.7826087, 3.2608696, 3, 3.6956522, 
    4.3478261, 4.6956522, 3.3913043, 4.5217391, 4.1304348, 3.7391304, 
    3.6956522, 5.8695652, 5.1304348, 4, 4.0869565, 3.6956522, 
    4, 3.9130435, 3.4782609, 2.6086957, 4.4782609, 3.4782609, 
    5.826087, 4.6956522, 5.7391304, 4.1304348, 2.826087, 5.1304348, 
    4.6521739, 4.826087, 2.0434783, 2.6956522, 5.3913043, 2.7826087, 
    3.1304348, 3.826087, 4.0869565, 5.5217391, 3.2173913, 4.9130435, 
    2.826087, 3.9565217, 3.9565217, 5.3913043, 4.826087, 3.3478261, 
    6.1304348, 5.6521739, 2.5652174, 2.3478261, 3.6521739, 3.2608696, 
    3.4782609, 4.173913, 4.0434783, 4.173913, 3.4347826, 3.3913043, 
    3.5217391, 5.2608696, 4.9130435, 2.6521739, 5.5217391, 3.3043478, 
    5.6956522, 3.6086957, 3.8695652, 6.826087, 4.7391304, 3.6086957, 
    3.7391304, 5.2608696, 3.4782609, 3.4782609, 3.1304348, 5.6521739, 
    5.6956522, 5.5652174, 4.6956522, 5.8695652, 5.1304348, 5.3478261, 
    5.7826087, 4.9565217, 4.6086957, 4.0869565, 5.5217391, 3.5652174, 
    4.173913, 6.6521739, 5.3913043, 3.5652174, 3.6086957, 4.1304348, 
    3.5652174, 5.5217391, 5.1304348, 5.5652174, 4.9130435, 4.2608696, 
    4.5217391, 5.8695652, 3.826087, 3, 6.3478261, 7.4347826, 
    4.173913, 5.6956522, 4.4782609, 3.2608696, 2.8695652, 4.5652174, 
    4.6956522, 3.5652174, 4.826087, 5.3043478, 5.5652174, 3.6956522, 
    4.0869565, 5.826087, 4.6086957, 3.7391304, 3.6521739, 5, 
    4, 5.1304348, 4.9130435, 3.3043478, 4.5217391, 4.5652174, 
    7.2608696, 4.9130435, 4.6956522, 3.4347826, 4.3913043, 3.3478261, 
    4.4347826, 6.2608696, 6.4347826, 6.0434783, 3.3043478, 3.826087, 
    5.3478261, 2.3913043, 5.6086957, 6.9565217, 4.5217391, 3.5652174, 
    5.1304348, 5.6521739, 5.7826087, 5.3913043, 5.3913043, 4.6956522, 
    3.6086957, 3, 2.826087, 2.173913, 4.9565217, 4.8695652, 4.0869565, 
    5.6086957, 4.173913, 4.4782609, 3.8695652, 3.826087, 4.4782609, 
    3.6086957, 4.3043478, 2.1304348, 2.826087, 2.8695652, 3.1304348, 
    4.1304348, 3.5652174, 4.6086957, 3.826087, 4.8695652, 5.4782609, 
    2.9565217, 3.2173913, 4.173913, 2.3913043, 3.5217391, 2.2173913, 
    2.2608696, 4.6956522, 3.5217391, 2.173913, 4.3478261, 2.4347826, 
    3.5217391, 1.3043478, 4.0434783, 4, 4.1304348, 2.5217391, 
    2.826087, 2.6521739, 3.5652174, 2.6956522, 2.6521739, 3.0869565, 
    2.6521739, 3.6956522, 2.7826087, 4.1304348, 2, 3.7391304, 
    3.826087, 3.8695652, 4.3478261, 3.4782609, 3.173913, 3.4782609, 
    5.2173913, 2.9130435, 4.6086957, 4.3913043, 1.8695652, 3.173913, 
    3.173913, 4.3913043, 5.3913043, 3.9130435, 3.8695652, 5.1304348, 
    2.9565217, 3.5217391, 2.9565217, 3.826087, 2.9565217, 2.4347826, 
    3.3043478, 5.6521739, 3.6521739, 4.7391304, 4.7391304, 6.4782609, 
    4.8695652, 4.4782609, 5.826087, 3.6956522, 4, 4.7826087, 
    3.6521739, 4, 5.7391304, 5.7826087, 6.0434783, 5.7826087, 
    4.173913, 5.1304348, 3.4782609, 3.3913043, 4.4347826, 5, 
    4.1304348, 2.9565217, 3.7826087, 4.3478261, 4.826087, 3.3913043, 
    5.0869565, 4.173913, 6.3043478, 4.3043478, 4.2173913, 5, 
    4.6086957, 3, 5.8695652, 3.6956522, 4.7391304, 4, 3.3913043, 
    3.5652174, 4.6086957, 3.6521739, 3.4782609, 2.3913043, 3.3478261, 
    2.7826087, 4.2608696, 3.4782609, 3.3478261, 5.8695652, 5.2173913, 
    2.4347826, 5.826087, 4.173913, 5.4782609, 3.3913043, 4.173913, 
    3.0434783, 5.0869565, 4.6086957, 4, 5.0869565, 4.0869565), 
    x8 = c(5.75, 6.25, 3.9, 5.3, 6.3, 6.65, 6.2, 5.15, 4.65, 
    4.55, 5.7, 5.15, 5.2, 4.7, 4.35, 3.8, 6.65, 5.25, 4.85, 5.35, 
    4.6, 5.45, 4.6, 5.3, 4.6, 6.25, 5.1, 5.55, 5.85, 4.85, 6.95, 
    3.65, 4.3, 4.35, 5.2, 3.75, 4, 3.5, 5.45, 4.5, 5.1, 5.3, 
    4.75, 5.6, 5, 5, 6.35, 8, 5.9, 4.8, 5.05, 5.15, 4.2, 5.1, 
    4.8, 5.7, 5.25, 5.8, 4.55, 6.15, 6.2, 5.35, 3.85, 5.45, 4.5, 
    5.4, 5.75, 6.1, 5.7, 5.95, 5.5, 5.75, 7.35, 4.6, 5.7, 5.75, 
    5.7, 4, 7.35, 5.15, 6.45, 5.75, 5.2, 5.75, 4.85, 6.85, 5.4, 
    4.55, 5.55, 5.95, 7.5, 7.8, 6.4, 4.8, 5.35, 3.6, 5.85, 5.55, 
    6.1, 5.15, 5.3, 4.4, 6.25, 4.85, 6.2, 6.5, 5.7, 6.8, 6.4, 
    4.15, 3.9, 6, 5.35, 4.3, 3.95, 5.85, 6.85, 6.6, 5.2, 5.55, 
    6.4, 6.4, 7.6, 5.35, 6.9, 6.95, 5.65, 5.25, 5.1, 6.25, 7.8, 
    6.35, 6, 5.25, 6, 5.85, 5.1, 5.15, 6.55, 8.3, 5.25, 5.25, 
    7.1, 5.75, 5.6, 4.9, 6.25, 5, 6.3, 4.75, 7.55, 7.9, 7.5, 
    6.15, 5.6, 6.15, 4.1, 4.9, 4.3, 5.15, 6.1, 5.65, 6.95, 4.75, 
    5.7, 5.05, 5.35, 6.8, 5.4, 4.35, 4.2, 4, 5.65, 5.2, 5.5, 
    5.15, 4, 6.05, 5.75, 10, 5.8, 5.9, 6.05, 5.9, 6.4, 4.6, 4.7, 
    5.65, 5.8, 3.6, 7.2, 6.5, 4.8, 3.05, 5.55, 5.4, 4.6, 4.55, 
    4.2, 5, 5.2, 4.15, 3.85, 4.7, 3.5, 6.4, 3.7, 6.4, 3.6, 4.95, 
    5.7, 6.05, 6.05, 5.6, 4.2, 5.05, 5.45, 4.4, 6.35, 5.3, 5, 
    3.65, 5.05, 5.6, 5.95, 6.3, 5.8, 5.8, 4.1, 5.2, 4.85, 5.45, 
    4.55, 3.75, 5.7, 5.25, 6.35, 5.55, 7.15, 7.8, 6.3, 4.9, 5.1, 
    4.95, 4.75, 6.75, 6.6, 6.25, 5.9, 5.55, 5.5, 8.05, 6.1, 5.6, 
    4.75, 5.05, 5.65, 6.8, 5.95, 4, 4.65, 9.1, 6.25, 5.15, 5.4, 
    5.65, 5.85, 5.4, 6, 6.45, 5.3, 6.5, 7.1, 5.45, 7, 4.05, 4.45, 
    5.4, 7.15, 6.3, 5.85, 4, 4.7, 4.7, 6.6, 5.25, 5.95, 6.3, 
    6.55, 5.75, 5.5, 5.75, 6, 5.15, 4.85, 4.25, 5.6, 6.05, 6, 
    6.2, 6.95), x9 = c(6.3611111, 7.9166667, 4.4166667, 4.8611111, 
    5.9166667, 7.5, 4.8611111, 3.6666667, 7.3611111, 4.3611111, 
    4.3055556, 4.1388889, 5.8611111, 4.4444444, 5.8611111, 5.1388889, 
    5.25, 5.4444444, 5.75, 4.9166667, 5.3888889, 7, 5, 6.7777778, 
    4.1388889, 4.3333333, 4.5277778, 4.4166667, 8.6111111, 5.4444444, 
    5.9722222, 3.3611111, 4.8055556, 5.6388889, 4.8333333, 4.9166667, 
    5.3055556, 5.0833333, 5.1111111, 4.8888889, 4.6388889, 4.7777778, 
    2.7777778, 6.6666667, 6.8611111, 5, 6.2777778, 5.4444444, 
    6.0555556, 5.5277778, 5.5, 4.7777778, 5.3888889, 4.1944444, 
    4.4166667, 5.5555556, 5.6388889, 4.75, 4.8333333, 3.9444444, 
    6.1388889, 4.7777778, 5.3333333, 5.8333333, 5.0277778, 6.3055556, 
    6.1944444, 4.25, 3.9166667, 5.4166667, 4.6111111, 5.1666667, 
    5.9722222, 4.2777778, 4.5833333, 4.6666667, 6.4722222, 5.6388889, 
    5.75, 5.3333333, 6.0277778, 5.3055556, 5.7777778, 4.9722222, 
    4.5833333, 5.4722222, 5.9722222, 5.1388889, 4.8888889, 6.6666667, 
    5.4444444, 6.1111111, 5.7222222, 3.9444444, 3.7777778, 5.4444444, 
    4.2222222, 7.2222222, 4.6111111, 5.75, 6.25, 6.5833333, 4.1111111, 
    4.8333333, 6.0277778, 6.1666667, 5.1944444, 7, 7.5277778, 
    3.3611111, 4.8611111, 5.4444444, 5.4444444, 6, 6.3333333, 
    5.4166667, 5, 6.4444444, 5.1666667, 5.4444444, 6.8611111, 
    3.3055556, 6.5, 4.7777778, 6.3888889, 5.6666667, 4.9166667, 
    4.9722222, 5.7777778, 6.3055556, 7, 7.1944444, 4.8055556, 
    3.7222222, 6.1666667, 6.1111111, 5.4444444, 4.5555556, 6.8888889, 
    7.0833333, 6.2222222, 5.7222222, 5.7777778, 6.6111111, 5.9722222, 
    3.8611111, 6.3055556, 4.75, 5.4722222, 5.2222222, 6.1666667, 
    6.9444444, 5.4166667, 5.1944444, 4.1388889, 4.6944444, 4.3333333, 
    5.4166667, 6.3333333, 4, 4.4444444, 5.5833333, 9.25, 4.8333333, 
    5.4722222, 4.9444444, 3.8055556, 4.2777778, 5.5833333, 4.0833333, 
    4.75, 3.4722222, 5.1666667, 6.1666667, 4.4722222, 5.6944444, 
    3.2777778, 6.25, 5.1388889, 6.5555556, 6.0833333, 5.3055556, 
    5, 4.9444444, 5.25, 5.0555556, 3.9722222, 5, 4.4166667, 4.5, 
    5.6944444, 5.5, 5.5277778, 3.1111111, 5.1388889, 4.1111111, 
    4.9444444, 4.8055556, 3.8055556, 5.9444444, 6.7777778, 3.9722222, 
    4.4166667, 4.2777778, 3.3333333, 5.6111111, 4.5833333, 3.8055556, 
    3.3611111, 5.9444444, 6.1944444, 6.1666667, 5.7222222, 6.3611111, 
    4.4722222, 5.1388889, 5.6944444, 5, 4.8611111, 4.7777778, 
    4.0277778, 3.6111111, 6.1111111, 3.2222222, 6.1111111, 6.7222222, 
    6.5555556, 7, 4.7222222, 5.8333333, 4.1388889, 5.3055556, 
    5.0277778, 4.9166667, 4.3333333, 6.6944444, 6.3888889, 5.5555556, 
    6.8333333, 6.8611111, 6.3055556, 4.6666667, 6.2222222, 5.25, 
    5.9722222, 5.5277778, 4.0833333, 6.4444444, 5.1944444, 6.5277778, 
    5.5277778, 6.9166667, 5.8888889, 3.6666667, 4.75, 4.9722222, 
    5.8333333, 7.3888889, 6.6666667, 3.4722222, 4.7222222, 6.3055556, 
    5.7222222, 5.5, 6.5833333, 5.7222222, 6.2777778, 5.9722222, 
    7, 5.0833333, 5.1944444, 5.5, 6.25, 6.1111111, 4.9444444, 
    4.1666667, 5.3055556, 5.0555556, 5.5555556, 5.9722222, 6.5277778, 
    4.2777778, 3.75, 5.25, 6.6666667, 5.6944444, 5.4166667, 5.6666667, 
    5.7222222, 5, 6.7777778, 4.8333333, 4.5, 6.3333333, 5.7777778, 
    5.6666667, 5.25, 6.0833333, 7.6111111, 4.3888889, 5.1666667
    )), class = "data.frame", row.names = c(NA, -301L))

SORENA · February 4, 2020, 5:16pm

Thanks, that's working around the problem. I may be required to solve the problem. R is tricky as hell.

nirgrahamuk · February 4, 2020, 5:20pm

I understand that you got error on lavaan referencing lack of mnormt.

It's not clear what error if any you got when installing mnormt. If yes, the details of the error. If no, can you load the mnormt library and use it ?

SORENA · February 4, 2020, 5:41pm

I used this line of code to install mnormt package :

> install.packages("mnormt", depencies = TRUE)

Then when I want to load the package, this error pops up.

Error in library(mnormt) : there is no package called ‘mnormt’

nirgrahamuk · February 4, 2020, 6:13pm

Check for this typo?

SORENA · February 4, 2020, 6:25pm

My bad, but when I try correctly, I still get the same error. Is it required that I should uninstall RStudio and reinstall again?

nirgrahamuk · February 4, 2020, 6:46pm

I doubt it.

Can you share here what gets printed when you install packages mnormt?

SORENA · February 4, 2020, 6:49pm

WARNING: Rtools is required to build R packages but is not currently installed. Please download and install the appropriate version of Rtools before proceeding:

https://cran.rstudio.com/bin/windows/Rtools/
Installing package into ‘C:/Users/name/Documents/R/win-library/3.6’
(as ‘lib’ is unspecified)

  There is a binary version available but the source
  version is later:
       binary source needs_compilation
mnormt  1.5-5  1.5-6              TRUE

installing the source package ‘mnormt’

trying URL 'https://cran.rstudio.com/src/contrib/mnormt_1.5-6.tar.gz'
Content type 'application/x-gzip' length 37884 bytes (36 KB)
downloaded 36 KB

* installing *source* package 'mnormt' ...
** package 'mnormt' successfully unpacked and MD5 sums checked
** using staged installation
** libs
C:/PROGRA~1/R/R-36~1.2/etc/x64/Makeconf:230: warning: overriding commands for target `.m.o'
C:/PROGRA~1/R/R-36~1.2/etc/x64/Makeconf:223: warning: ignoring old commands for target `.m.o'
make: *** No rule to make target `$(FCLIBS_XTRA)''.  Stop.
ERROR: compilation failed for package 'mnormt'
* removing 'C:/Users/Sorena/Documents/R/win-library/3.6/mnormt'
Warning in install.packages :
  installation of package ‘mnormt’ had non-zero exit status

The downloaded source packages are in
	‘C:\Users\name\AppData\Local\Temp\RtmpGGZm4Q\downloaded_packages’

nirgrahamuk · February 4, 2020, 6:51pm

if you want to compile from source, you will need to install Rtools (the 1st line warning)
you can choose to install the compiled binary, avoiding the source compiliation.
try

install.packages("mnormt",type="binary")

SORENA · February 4, 2020, 7:00pm

I appreciate. It solved the problem.

system · February 25, 2020, 7:00pm

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