[R] oddsratio epitool and chi-square

[David martin]

Here is a working snippet.

library(epitools)
mat <- matrix(c(10,15,60,25,98, 12,10,70,28,14, 9,11,68,10,12 
,8,13,20,11,58) ,ncol=2)
colnames(mat) <- c("treatmentA","treatmentB")
row.names(mat) <- paste("Cond",rep(1:10,1))
dimnames(mat) <- list("Condition" = row.names(mat), "instrument" = 
colnames(mat))

 > mat
          instrument
Condition treatmentA treatmentB
   Cond 1          10          9
   Cond 2          15         11
   Cond 3          60         68
   Cond 4          25         10
   Cond 5          98         12
   Cond 6          12          8
   Cond 7          10         13
   Cond 8          70         20
   Cond 9          28         11
   Cond 10         14         13

# I'm not sure how to use the rev option of the oddsration works here. 
I'm trying to see if any of the treatments has an effect on each 
condition, so for example if treatment A has an effect on cond1 compared 
to treatmentB. And so on for each condition.
I also don't understand why i get an NA value  on cond10 ???

 > oddsratio(mat,rev="r") . Shoudl this be rev="r" or rev="c"
$data
          instrument
Condition treatmentA treatmentB Total
   Cond 10         14         58    72
   Cond 9          28         11    39
   Cond 8          70         20    90
   Cond 7          10         13    23
   Cond 6          12          8    20
   Cond 5          98         12   110
   Cond 4          25         10    35
   Cond 3          60         68   128
   Cond 2          15         11    26
   Cond 1          10          9    19
   Total          342        220   562

$measure
          odds ratio with 95% C.I.
Condition   estimate      lower      upper
   Cond 10 1.00000000         NA         NA
   Cond 9  0.09829116 0.03774410 0.23797549
   Cond 8  0.07099961 0.03179722 0.14918984
   Cond 7  0.31836593 0.11348206 0.89217010
   Cond 6  0.16616586 0.05412347 0.48011838
   Cond 5  0.03081892 0.01269306 0.06870094
   Cond 4  0.10021240 0.03728880 0.24932078
   Cond 3  0.27705710 0.13577945 0.53625865
   Cond 2  0.18189409 0.06613614 0.47770002
   Cond 1  0.22261481 0.07313306 0.65711936

$p.value
          two-sided
Condition   midp.exact fisher.exact   chi.square
   Cond 10           NA           NA           NA
   Cond 9  8.154112e-08 1.049524e-07 5.662609e-08
   Cond 8  5.306866e-14 6.524468e-14 1.539341e-13
   Cond 7  2.978326e-02 2.860464e-02 2.092707e-02
   Cond 6  8.811686e-04 1.259777e-03 3.660559e-04
   Cond 5  0.000000e+00 3.867056e-22 3.600564e-21
   Cond 4  2.707171e-07 3.071608e-07 1.590623e-07
   Cond 3  9.355292e-05 1.212804e-04 1.149120e-04
   Cond 2  5.085059e-04 7.732183e-04 2.499965e-04
   Cond 1  6.702975e-03 6.992229e-03 3.499738e-03

$correction
[1] FALSE

attr(,"method")
[1] "median-unbiased estimate & mid-p exact CI"
 >