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Error when summarize tssem1 results

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anyuliu's picture
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Joined: 12/11/2018 - 12:57
Error when summarize tssem1 results
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I have a 26*26 matrix for 10 studies with many missing values. It costed a few hours to run the random effect model of tssem1. When I summarized the results by "summary(random1)" , the error "Error in chol.default(V) : 'a' must have dims > 0" appereared. I also noiced that many correlications are presented as "0.1".

Could anyone help to fix the error? May I know that those "0.1"s in the correlaiton matrix are resulted from the many "NA"s in the input matrices? Thank you for your great help.

The data and code are attached.

Regrads
Annyu

Mike Cheung's picture
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Joined: 10/08/2009 - 22:37
There is almost no data in

There is almost no data in the dataset. It is impossible to make it work.

Moreover, the correlation matrices are not symmetric. The upper triangles are all zeros.

pattern.na(mydatar, show.na = FALSE)
    x1 x2 x3 x4 x5 x6 x7 x8 x9 x10 x11 x12 x13 x14 x15 x16 x17 x18 x19 x20 x21 x22 x23 x24 x25 x26 x27
x1   0  0  0  0  0  0  0  0  0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
x2   1  0  0  0  0  0  0  0  0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
x3   1  0  0  0  0  0  0  0  0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
x4   0  1  0  0  0  0  0  0  0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
x5   0  1  0  0  0  0  0  0  0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
x6   0  1  0  0  0  0  0  0  0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
x7   0  1  0  0  0  0  0  0  0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
x8   0  1  0  0  0  0  0  0  0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
x9   0  0  1  0  0  0  0  0  0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
x10  0  0  2  0  0  0  0  0  0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
x11  0  0  1  0  0  0  0  0  1   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
x12  1  0  1  0  0  0  1  0  1   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
x13  0  1  0  0  0  0  0  0  0   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
x14  1  0  2  0  1  1  1  1  0   1   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0
x15  0  0  0  0  0  0  0  0  0   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
x16  0  0  3  1  0  2  2  0  0   0   0   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0
x17  0  0  1  0  0  0  0  0  0   0   0   0   0   0   0   2   0   0   0   0   0   0   0   0   0   0   0
x18  1  0  1  0  0  0  1  0  0   0   0   1   2   1   1   1   1   0   0   0   0   0   0   0   0   0   0
x19  0  0  0  0  0  0  0  0  0   0   0   0   0   0   1   0   1   1   0   0   0   0   0   0   0   0   0
x20  0  0  1  0  0  0  0  0  0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
x21  0  0  1  0  0  0  0  0  0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
x22  0  0  0  0  0  0  0  0  0   0   0   0   0   0   0   2   0   0   0   0   0   0   0   0   0   0   0
x23  0  0  1  0  0  0  0  0  0   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0
x24  0  0  0  0  0  0  0  0  0   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0
x25  0  0  0  0  0  0  0  0  0   0   0   1   0   0   0   0   0   1   0   0   0   0   0   0   0   0   0
x26  0  0  0  0  0  0  0  0  0   0   0   1   0   0   0   0   0   1   0   0   0   0   0   0   0   0   0
x27  0  0  0  0  0  0  0  0  0   0   0   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0

Mike