r - Can corr.test be used for any dataframe? -


i trying find correlations , p-values between variables in dataframe (df1) using corr.test in psych package. variables in dataframe integers , there no nas. when run corr.test(df1), there error message.

error in data.frame(lower = lower, r = r[lower.tri(r)], upper = upper,  :    arguments imply differing number of rows: 0, 28 

i tried run example (corr.test(sat.act)) in psych package , there no error. new r, can tell me wrong dataframe.

> head(df1)   s1.pre s2.pre s1.post s2.post v1.pre v2.pre v1.post v2.post 1     21     31      25      35      7      1      19       4 2     15     26      21      29     13     11      16      14 3     18     27      23      31      8      2       3       3 4     17     31      18      39     13     11      15      14 5     15     26      16      29     26     15      32      20 6     17     28      16      28      2      4       2       7  > dput(head(df1)) structure(list(s1.pre = c(21l, 15l, 18l, 17l, 15l, 17l), s2.pre = c(31l,  26l, 27l, 31l, 26l, 28l), s1.post = c(25l, 21l, 23l, 18l, 16l,  16l), s2.post = c(35l, 29l, 31l, 39l, 29l, 28l), v1.pre = c(7l,  13l, 8l, 13l, 26l, 2l), v2.pre = c(1l, 11l, 2l, 11l, 15l, 4l),  v1.post = c(19l, 16l, 3l, 15l, 32l, 2l), v2.post = c(4l,  14l, 3l, 14l, 20l, 7l)), .names = c("s1.pre", "s2.pre", "s1.post",  "s2.post", "v1.pre", "v2.pre", "v1.post", "v2.post"), row.names = c(na,  6l), class = "data.frame")  > sapply(df1, class) s1.pre    s2.pre   s1.post   s2.post    v1.pre    v2.pre   v1.post   v2.post  "integer" "integer" "integer" "integer" "integer" "integer" "integer" "integer"  

i contacted william revelle - author of psych package , here said:

mark, unfotunately found bug introduced 1.4.3. 1.4.4 go out cran weekend. in meantime can fix @ http://personality-project.org/r (choose source other repository if using mac) or http://personality-project.org/r/src/contrib , zip file if using pc. otherwise, wait until next week. sorry problem. still work long have unequal number of subjects or missing data.


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