Hello,
I know there must be a simple soluton to this problem but it eludes me
currently.
My data is partitioned into two subsets, each subset has a common column
factor but with varying levels:
levels(fdf_ghc$AgeDemo)
[1] "26TO35" "36TO45" "46TO55" "56TO65" "66TO75" "76TO85"
levels(fdf_ghcnull$AgeDemo)
[1] "26TO35" "36TO45" "46TO55" "56TO65" "66TO75" "76TO85" "86TO100"
table(fdf_ghc$AgeDemo)
26TO35 36TO45 46TO55 56TO65 66TO75 76TO85
6 14 21 31 19 14
table(fdf_ghcnull$AgeDemo)
26TO35 36TO45 46TO55 56TO65 66TO75 76TO85 86TO100
5 5 10 7 8 4 1
I need to construct a common contingency table from the two lists, but rbind
recycles values due to the differing levels:
rbind(table(fdf_ghc$AgeDemo), table(fdf_ghcnull$AgeDemo))
26TO35 36TO45 46TO55 56TO65 66TO75 76TO85 86TO100
[1,] 6 14 21 31 19 14 6
[2,] 5 5 10 7 8 4 1
Warning message:
In rbind(table(fdf_ghc$AgeDemo), table(fdf_ghcnull$AgeDemo)) :
number of columns of result is not a multiple of vector length (arg 1)
I need something I can pass to fisher.test() or chisq.test().
Anybody have any hints?
Thanks,
Ben
[[alternative HTML version deleted]]
______________________________________________
[email protected] mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
