For a given object it will look for the column named "p adj" or "difference" and extract its value keeping its names
Usage
extract_p(x)
# Default S3 method
extract_p(x)
# S3 method for class 'TukeyHSD'
extract_p(x)
# S3 method for class 'mc'
extract_p(x)Methods (by class)
extract_p(default):extract_p(TukeyHSD): extract p values from a TukeyHSD objectextract_p(mc):
Examples
experiment <- data.frame(treatments = gl(11, 20, labels = c("dtl", "ctrl", "treat1",
"treat2", "treatA2", "treatB", "treatB2",
"treatC", "treatD", "treatA1", "treatX")),
y = c(rnorm(20, 10, 5), rnorm(20, 20, 5), rnorm(20, 22, 5), rnorm(20, 24, 5),
rnorm(20, 35, 5), rnorm(20, 37, 5), rnorm(20, 40, 5), rnorm(20, 43, 5),
rnorm(20, 45, 5), rnorm(20, 60, 5), rnorm(20, 60, 5)))
exp_tukey <- TukeyHSD(exp_aov <- aov(y ~ treatments, data = experiment))
extract_p(exp_tukey)
#> $treatments
#> ctrl-dtl treat1-dtl treat2-dtl treatA2-dtl treatB-dtl
#> 1.449127e-09 2.071676e-13 8.482104e-14 0.000000e+00 0.000000e+00
#> treatB2-dtl treatC-dtl treatD-dtl treatA1-dtl treatX-dtl
#> 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> treat1-ctrl treat2-ctrl treatA2-ctrl treatB-ctrl treatB2-ctrl
#> 9.053584e-01 2.199649e-01 8.504308e-14 9.081624e-14 0.000000e+00
#> treatC-ctrl treatD-ctrl treatA1-ctrl treatX-ctrl treat2-treat1
#> 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 9.881220e-01
#> treatA2-treat1 treatB-treat1 treatB2-treat1 treatC-treat1 treatD-treat1
#> 1.147971e-13 3.318679e-12 5.506706e-14 0.000000e+00 0.000000e+00
#> treatA1-treat1 treatX-treat1 treatA2-treat2 treatB-treat2 treatB2-treat2
#> 0.000000e+00 0.000000e+00 3.184941e-11 2.915289e-09 9.436896e-14
#> treatC-treat2 treatD-treat2 treatA1-treat2 treatX-treat2 treatB-treatA2
#> 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 9.995551e-01
#> treatB2-treatA2 treatC-treatA2 treatD-treatA2 treatA1-treatA2 treatX-treatA2
#> 6.057976e-01 1.138772e-03 3.761067e-04 0.000000e+00 0.000000e+00
#> treatB2-treatB treatC-treatB treatD-treatB treatA1-treatB treatX-treatB
#> 1.558948e-01 4.115310e-05 1.161865e-05 0.000000e+00 0.000000e+00
#> treatC-treatB2 treatD-treatB2 treatA1-treatB2 treatX-treatB2 treatD-treatC
#> 4.583470e-01 2.894728e-01 0.000000e+00 3.219647e-14 1.000000e+00
#> treatA1-treatC treatX-treatC treatA1-treatD treatX-treatD treatX-treatA1
#> 4.996004e-14 1.032507e-13 6.639134e-14 1.633138e-13 6.433673e-01
#>
if(require(pgirmess)){
extract_p(kruskalmc(y ~ treatments, data = experiment))
}
#> Loading required package: pgirmess
#> dtl-ctrl dtl-treat1 dtl-treat2 dtl-treatA2 dtl-treatB
#> FALSE FALSE FALSE TRUE TRUE
#> dtl-treatB2 dtl-treatC dtl-treatD dtl-treatA1 dtl-treatX
#> TRUE TRUE TRUE TRUE TRUE
#> ctrl-treat1 ctrl-treat2 ctrl-treatA2 ctrl-treatB ctrl-treatB2
#> FALSE FALSE TRUE FALSE TRUE
#> ctrl-treatC ctrl-treatD ctrl-treatA1 ctrl-treatX treat1-treat2
#> TRUE TRUE TRUE TRUE FALSE
#> treat1-treatA2 treat1-treatB treat1-treatB2 treat1-treatC treat1-treatD
#> FALSE FALSE TRUE TRUE TRUE
#> treat1-treatA1 treat1-treatX treat2-treatA2 treat2-treatB treat2-treatB2
#> TRUE TRUE FALSE FALSE TRUE
#> treat2-treatC treat2-treatD treat2-treatA1 treat2-treatX treatA2-treatB
#> TRUE TRUE TRUE TRUE FALSE
#> treatA2-treatB2 treatA2-treatC treatA2-treatD treatA2-treatA1 treatA2-treatX
#> FALSE FALSE FALSE TRUE TRUE
#> treatB-treatB2 treatB-treatC treatB-treatD treatB-treatA1 treatB-treatX
#> FALSE FALSE FALSE TRUE TRUE
#> treatB2-treatC treatB2-treatD treatB2-treatA1 treatB2-treatX treatC-treatD
#> FALSE FALSE TRUE FALSE FALSE
#> treatC-treatA1 treatC-treatX treatD-treatA1 treatD-treatX treatA1-treatX
#> FALSE FALSE FALSE FALSE FALSE