Functions to combine and adjust the outputs 3-table methods
combine.4thcorner.RdFunctions to combine and adjust the outputs of the fourthcorner and
randtest.rlq functions created using permutational models 2 and
4 (sequential approach).
Usage
combine.randtest.rlq(obj1, obj2, ...)
combine.4thcorner(four1,four2)
p.adjust.4thcorner(x, p.adjust.method.G = p.adjust.methods,
p.adjust.method.D = p.adjust.methods, p.adjust.D = c("global",
"levels"))Arguments
- four1
an object of the class 4thcorner created with modeltype = 2 (or 4)
- four2
an object of the class 4thcorner created with modeltype = 4 (or 2)
- obj1
an object created with
randtest.rlqand modeltype = 2 (or 4)- obj2
an object created with
randtest.rlqand modeltype = 4 (or 2)- x
an object of the class 4thcorner
- p.adjust.method.G
a string indicating a method for multiple adjustment used for output tabG, see
p.adjust.methodsfor possible choices- p.adjust.method.D
a string indicating a method for multiple adjustment used for output tabD/tabD2, see
p.adjust.methodsfor possible choices- p.adjust.D
a string indicating if multiple adjustment for tabD/tabD2 should be done globally or only between levels of a factor ("levels", as in the original paper of Legendre et al. 1997)
- ...
further arguments passed to or from other methods
Details
The functions combines the outputs of two objects (created by
fourthcorner and randtest.rlq functions) as described in
Dray and Legendre (2008) and ter Braak et al (2012).
Value
The functions return objects of the same class than their argument. They simply create a new object where pvalues are equal to the maximum of pvalues of the two arguments.
References
Dray, S. and Legendre, P. (2008) Testing the species traits-environment relationships: the fourth-corner problem revisited. Ecology, 89, 3400–3412.
ter Braak, C., Cormont, A., and Dray, S. (2012) Improved testing of species traits-environment relationships in the fourth corner problem. Ecology, 93, 1525–1526.
Author
Stéphane Dray stephane.dray@univ-lyon1.fr
Examples
data(aravo)
four2 <- fourthcorner(aravo$env, aravo$spe, aravo$traits, nrepet=99,modeltype=2)
four4 <- fourthcorner(aravo$env, aravo$spe, aravo$traits, nrepet=99,modeltype=4)
four.comb <- combine.4thcorner(four2,four4)
## or directly :
## four.comb <- fourthcorner(aravo$env, aravo$spe, aravo$traits, nrepet=99,modeltype=6)
summary(four.comb)
#> Fourth-corner Statistics
#> ------------------------
#> Permutation method Comb. 2 and 4 ( 99 permutations)
#>
#> Adjustment method for multiple comparisons: holm
#> Test Stat Obs Std.Obs Alter Pvalue Pvalue.adj
#> 1 Aspect / Height r -0.045735104 -1.16056804 two-sided 0.28 1.00
#> 2 Slope / Height r 0.094917344 2.10616338 two-sided 0.03 1.00
#> 3 Form / Height F 15.219879474 2.61169655 greater 0.03 1.00
#> 4 PhysD / Height r 0.113164322 1.95670623 two-sided 0.04 1.00
#> 5 ZoogD / Height F 15.227717714 2.15749663 greater 0.04 1.00
#> 6 Snow / Height r -0.271739531 -5.94003192 two-sided 0.01 0.48
#> 7 Aspect / Spread r -0.044170141 -1.50519083 two-sided 0.14 1.00
#> 8 Slope / Spread r -0.017325425 -0.58484575 two-sided 0.60 1.00
#> 9 Form / Spread F 5.548173196 0.15996975 greater 0.31 1.00
#> 10 PhysD / Spread r -0.051680330 -0.70770496 two-sided 0.52 1.00
#> 11 ZoogD / Spread F 0.120114487 -1.09483273 greater 0.97 1.00
#> 12 Snow / Spread r 0.065634673 0.61870811 two-sided 0.54 1.00
#> 13 Aspect / Angle r -0.090837201 -1.78670739 two-sided 0.08 1.00
#> 14 Slope / Angle r 0.100281966 2.18691561 two-sided 0.03 1.00
#> 15 Form / Angle F 30.664664234 7.65142303 greater 0.01 0.48
#> 16 PhysD / Angle r 0.221380084 4.18396355 two-sided 0.01 0.48
#> 17 ZoogD / Angle F 28.051040522 3.40460234 greater 0.03 1.00
#> 18 Snow / Angle r -0.269613756 -2.84488459 two-sided 0.02 0.72
#> 19 Aspect / Area r 0.031237858 0.68772978 two-sided 0.47 1.00
#> 20 Slope / Area r -0.003864605 -0.06761600 two-sided 0.91 1.00
#> 21 Form / Area F 13.609309880 1.99637785 greater 0.04 1.00
#> 22 PhysD / Area r -0.134371361 -2.12848630 two-sided 0.03 1.00
#> 23 ZoogD / Area F 49.672266332 12.49633111 greater 0.01 0.48
#> 24 Snow / Area r -0.024574466 -0.64262951 two-sided 0.51 1.00
#> 25 Aspect / Thick r -0.058466142 -1.84179759 two-sided 0.08 1.00
#> 26 Slope / Thick r 0.074151819 1.69103722 two-sided 0.13 1.00
#> 27 Form / Thick F 14.204346501 2.39286926 greater 0.04 1.00
#> 28 PhysD / Thick r 0.143161734 2.55814626 two-sided 0.03 1.00
#> 29 ZoogD / Thick F 2.825887968 0.21135429 greater 0.29 1.00
#> 30 Snow / Thick r -0.154660144 -1.69220168 two-sided 0.09 1.00
#> 31 Aspect / SLA r -0.007694551 -0.12131481 two-sided 0.90 1.00
#> 32 Slope / SLA r -0.235864886 -4.18124897 two-sided 0.01 0.48
#> 33 Form / SLA F 100.787472071 13.95082688 greater 0.01 0.48
#> 34 PhysD / SLA r -0.275524984 -4.33405203 two-sided 0.01 0.48
#> 35 ZoogD / SLA F 0.984301951 -0.93596671 greater 0.86 1.00
#> 36 Snow / SLA r 0.481181824 7.82597644 two-sided 0.01 0.48
#> 37 Aspect / N_mass r -0.061575524 -1.14795000 two-sided 0.33 1.00
#> 38 Slope / N_mass r -0.201308154 -3.73690796 two-sided 0.01 0.48
#> 39 Form / N_mass F 70.042280400 10.93881391 greater 0.01 0.48
#> 40 PhysD / N_mass r -0.212434381 -3.83482413 two-sided 0.01 0.48
#> 41 ZoogD / N_mass F 10.300092724 0.61495960 greater 0.23 1.00
#> 42 Snow / N_mass r 0.429271163 7.47210139 two-sided 0.01 0.48
#> 43 Aspect / Seed r 0.011598435 0.49474310 two-sided 0.68 1.00
#> 44 Slope / Seed r 0.077073974 1.72751152 two-sided 0.11 1.00
#> 45 Form / Seed F 5.561841954 -0.02385651 greater 0.46 1.00
#> 46 PhysD / Seed r 0.078156305 1.42319208 two-sided 0.16 1.00
#> 47 ZoogD / Seed F 3.369068338 1.39648268 greater 0.11 1.00
#> 48 Snow / Seed r -0.177640721 -1.83548235 two-sided 0.08 1.00
#>
#> ---
#> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
plot(four.comb, stat = "G")
