exact.pval1s | R Documentation |
p
-value correction to the one-sided version of exact NNCT testIn using Fisher's exact test on the 2 \times 2
nearest neighbor contingency tables (NNCTs) a correction
may be needed for the p
-value. For the one-sided alternatives, the probabilities of
more extreme tables are summed up, including or excluding the
probability of the table itself (or some middle way).
Let the probability of the contingency table itself be p_t=f(n_{11}|n_1,n_2,c_1;\theta_0)
where \theta_0=(n_1-1)(n_2-1)/(n_1 n_2)
which is the odds ratio
under RL or CSR independence and
f
is the probability mass function of the hypergeometric distribution.
For testing the one-sided alternative H_o:\,\theta=\theta_0
versus H_a:\,\theta>\theta_0
,
we consider the following four methods in calculating the p
-value:
[(i)] with S=\{t:\,t \geq n_{11}\}
, we get the
table-inclusive version which is denoted as p^>_{inc}
,
[(ii)] with S=\{t:\,t> n_{11}\}
, we get the
table-exclusive version, denoted as p^>_{exc}
.
[(iii)] Using p=p^>_{exc}+p_t/2
, we get the mid-p
version, denoted as p^>_{mid}
.
[(iv)] We can also use Tocher corrected version which is denoted as p^>_{Toc}
(see tocher.cor
for details).
See (\insertCiteceyhan:exact-NNCT;textualnnspat) for more details.
exact.pval1s(ptable, pval, type = "inc")
ptable |
Probability of the observed |
pval |
Table inclusive |
type |
The type of the |
A modified p
-value based on the correction specified in type
.
Elvan Ceyhan
exact.pval2s
and tocher.cor
ct<-matrix(sample(20:40,4),ncol=2)
ptab<-prob.nnct(ct)
pv<-.3
exact.pval1s(ptab,pv)
exact.pval1s(ptab,pv,type="exc")
exact.pval1s(ptab,pv,type="mid")
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