I have a question concerning the Wilcoxon signed-rank test, and 
specifically, which R subroutine I should use for my particular dataset. 
There are three different commands in R (that I'm aware of) that calculate 
the Wilcoxon signed-rank test; wilcox.test, wilcox.exact, and 
wilcoxsign_test. When I run the three commands on the same dataset, I get 
different p-values. I'm hoping that someone can give me guidance on the 
strengths and weaknesses of each command, why they produce different 
p-values, and which one is the most appropriate for my particular needs.

First, let me describe the dataset I am working with. The project I am 
working on collected water samples from groups/networks of about 30 water 
wells and analyzed them for nitrate, major ions, and other chemical 
constituents. We revisited those same wells about 10 years later and 
analyzed the water samples for the same chemical constituents. I now have 
a paired dataset, and the question I would like to answer is whether there 
was a "significant" change in concentrations of those chemical 
constituents (such as nitrate or chloride). Concentrations measured in 
water from some wells have increased, some have decreased, and some have 
stayed the same over the ten-year time period. In water from some wells, 
the concentrations were below the laboratory detection limits, so those 
concentrations are "tied" at the reporting level. The following is an 
example of the data I am evaluating. 

x <- c(13.60, 9.10, 22.01, 9.08, 1.97, 2.81, 0.66, 0.97, 0.21, 2.23, 0.08, 
0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 
0.06, 0.06, 3.44, 15.18, 5.25, 4.27, 17.81)
y <- c( 4.32, 3.39, 16.36, 7.10, 0.08, 2.02, 0.19, 0.59, 0.06, 2.15, 0.06, 
0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 
0.06, 0.06, 4.02, 16.13, 7.30, 7.98, 24.37)

The nonparametric Wilcoxon signed-rank test seems to be the most 
appropriate test for these data. There are two different methods to 
calculate the signed-rank test. The first is by Wilcoxon (1945), who 
discards any tied data and then calculates the signed ranks. The second 
method incorporates tied values in the ranking procedure (see J.W. Pratt, 
1959, Remarks on zeros and ties in the Wilcoxon signed rank procedure: 
Journal of the American Statistical Association, Vol. 54, No. 287, pp. 
655-667). There are two commands in R that calculate the original method 
by Wilcoxon (that I know of), wilcox.test and wilcoxsign_test (make sure 
to include the argument "zero.method = c("Wilcoxon")"). There are two 
other commands in R that incorporate ties in the signed-rank test, 
wilcox.exact and wilcoxsign_test (make sure to include the 
argument"zero.method = c("Pratt")").

Here's my problem. I get different p-values from each of the 4 signed-rank 
tests in R, and I don't know which one to believe. Wilcox.test and 
wilcoxsign_test(zero.method = c("Wilcoxon") calculate the standard 
Wilcoxon signed-rank test. Even though they are not designed to deal with 
tied data, they should at least calculate the same p-value, but they do 
not. I ran the same datasets in SYSTAT and Minitab to check on the results 
from R. Minitab gives the same results as wilcox.test, and SYSTAT gives 
the same results as wilcoxsign_test(zero.method = c("Wilcoxon"). 
Similarly, wilcox.exact and wilcoxsign_test(zero.method = c("Pratt")) are 
designed to incorporate ties, but they give different p-values from each 
other. The signed-rank test procedure is relatively straightforward, so 
I'm surprised I'm not getting identical results. 

To check on these R commands, I calculated the signed-rank tests using the 
dataset shown on page 658-659 of Pratt (1959). These R routines do not 
produce the same results as that listed in Pratt, which makes me think 
that the R routines are not calculating the statistics correctly. The 
following text shows the commands I use in R to calculate the signed-rank 
test using these different R commands:

Thanks in advance for any assistance.

--Mike

#################################################################################
library(exactRankTests) #this loads the package for calculating the 
modified signed-rank test
library(coin) #this adds additional routines for the wilcoxon signed-rank 
test and the Pratt signed-rank test
#
# Data from Page 658 of Pratt
x <- c(1, 1, 1, 1, 1, 7, 10, 12, 13, 16, 17)
y <- c(1, 1, 3, 4, 6, 1,  1,  1,  1,  1, 1)
#
# STANDARD WILCOXON SIGNED RANK USING WILCOX.TEST
wilcox.test(x, y, alternative='two.sided', paired=TRUE)
# STANDARD WILCOXON SIGNED-RANK USING WILCOXSIGN_TEST. 
wilcoxsign_test (x ~ y, zero.method = c("Wilcoxon"))
#
#
# MODIFIED WILCOXON SIGNED-RANK USING WILCOX.EXACT
wilcox.exact(x, y, alternative='two.sided', paired=TRUE, mu=0)
# PRATT SIGNED-RANK TEST
wilcoxsign_test (x ~ y, zero.method = c("Pratt"))
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