extract_p.RdFor a given object it will look for the column named "p adj" or "difference" and extract its value keeping its names
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)A named vector with p-values or logical values.
extract_p(default):
extract_p(TukeyHSD): extract p values from a TukeyHSD object
extract_p(mc):
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
#> 1.181586e-08 4.181100e-13 9.414691e-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
#> 8.108838e-01 1.466757e-01 8.948398e-14 9.481305e-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 9.901471e-01
#> treatA2-treat1 treatB-treat1 treatB2-treat1 treatC-treat1 treatD-treat1
#> 8.544276e-13 1.108336e-12 8.526513e-14 0.000000e+00 0.000000e+00
#> treatA1-treat1 treatX-treat1 treatA2-treat2 treatB-treat2 treatB2-treat2
#> 0.000000e+00 0.000000e+00 6.511587e-10 8.485427e-10 9.392487e-14
#> treatC-treat2 treatD-treat2 treatA1-treat2 treatX-treat2 treatB-treatA2
#> 7.993606e-15 0.000000e+00 0.000000e+00 0.000000e+00 1.000000e+00
#> treatB2-treatA2 treatC-treatA2 treatD-treatA2 treatA1-treatA2 treatX-treatA2
#> 5.993468e-01 8.528938e-04 4.826761e-05 0.000000e+00 0.000000e+00
#> treatB2-treatB treatC-treatB treatD-treatB treatA1-treatB treatX-treatB
#> 5.671536e-01 7.079746e-04 3.913932e-05 0.000000e+00 0.000000e+00
#> treatC-treatB2 treatD-treatB2 treatA1-treatB2 treatX-treatB2 treatD-treatC
#> 4.161509e-01 1.037188e-01 0.000000e+00 1.354472e-14 9.998833e-01
#> treatA1-treatC treatX-treatC treatA1-treatD treatX-treatD treatX-treatA1
#> 2.731149e-14 8.903989e-14 7.926992e-14 2.726708e-13 5.929523e-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 TRUE 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 TRUE FALSE
#> treatC-treatA1 treatC-treatX treatD-treatA1 treatD-treatX treatA1-treatX
#> FALSE FALSE FALSE FALSE FALSE