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 -1.07962114 two-sided 0.32 1.00
#> 2 Slope / Height r 0.094917344 1.94978334 two-sided 0.08 1.00
#> 3 Form / Height F 15.219879474 3.23795242 greater 0.02 0.72
#> 4 PhysD / Height r 0.113164322 1.98108834 two-sided 0.04 1.00
#> 5 ZoogD / Height F 15.227717714 1.67606996 greater 0.11 1.00
#> 6 Snow / Height r -0.271739531 -2.80497356 two-sided 0.02 0.72
#> 7 Aspect / Spread r -0.044170141 -1.55510898 two-sided 0.11 1.00
#> 8 Slope / Spread r -0.017325425 -0.77364418 two-sided 0.47 1.00
#> 9 Form / Spread F 5.548173196 0.22476723 greater 0.27 1.00
#> 10 PhysD / Spread r -0.051680330 -0.93941452 two-sided 0.30 1.00
#> 11 ZoogD / Spread F 0.120114487 -1.01756970 greater 0.93 1.00
#> 12 Snow / Spread r 0.065634673 0.73407808 two-sided 0.49 1.00
#> 13 Aspect / Angle r -0.090837201 -1.90874050 two-sided 0.07 1.00
#> 14 Slope / Angle r 0.100281966 2.29945221 two-sided 0.04 1.00
#> 15 Form / Angle F 30.664664234 7.89119483 greater 0.01 0.48
#> 16 PhysD / Angle r 0.221380084 4.55626644 two-sided 0.01 0.48
#> 17 ZoogD / Angle F 28.051040522 3.16689819 greater 0.02 0.72
#> 18 Snow / Angle r -0.269613756 -2.60618791 two-sided 0.02 0.72
#> 19 Aspect / Area r 0.031237858 0.74372511 two-sided 0.56 1.00
#> 20 Slope / Area r -0.003864605 -0.03480649 two-sided 0.98 1.00
#> 21 Form / Area F 13.609309880 2.64227747 greater 0.03 0.93
#> 22 PhysD / Area r -0.134371361 -2.07282497 two-sided 0.03 0.93
#> 23 ZoogD / Area F 49.672266332 14.29032202 greater 0.01 0.48
#> 24 Snow / Area r -0.024574466 -0.43634412 two-sided 0.59 1.00
#> 25 Aspect / Thick r -0.058466142 -1.38136315 two-sided 0.17 1.00
#> 26 Slope / Thick r 0.074151819 1.49324698 two-sided 0.14 1.00
#> 27 Form / Thick F 14.204346501 9.41120270 greater 0.01 0.48
#> 28 PhysD / Thick r 0.143161734 2.40103522 two-sided 0.02 0.72
#> 29 ZoogD / Thick F 2.825887968 0.57502021 greater 0.19 1.00
#> 30 Snow / Thick r -0.154660144 -1.67889659 two-sided 0.11 1.00
#> 31 Aspect / SLA r -0.007694551 0.05042614 two-sided 0.97 1.00
#> 32 Slope / SLA r -0.235864886 -3.71571891 two-sided 0.01 0.48
#> 33 Form / SLA F 100.787472071 17.10157728 greater 0.01 0.48
#> 34 PhysD / SLA r -0.275524984 -4.78051167 two-sided 0.01 0.48
#> 35 ZoogD / SLA F 0.984301951 -0.87404483 greater 0.89 1.00
#> 36 Snow / SLA r 0.481181824 7.94830614 two-sided 0.01 0.48
#> 37 Aspect / N_mass r -0.061575524 -0.92404445 two-sided 0.36 1.00
#> 38 Slope / N_mass r -0.201308154 -3.61596658 two-sided 0.01 0.48
#> 39 Form / N_mass F 70.042280400 13.06958338 greater 0.01 0.48
#> 40 PhysD / N_mass r -0.212434381 -3.96829951 two-sided 0.01 0.48
#> 41 ZoogD / N_mass F 10.300092724 0.72853295 greater 0.17 1.00
#> 42 Snow / N_mass r 0.429271163 7.98893996 two-sided 0.01 0.48
#> 43 Aspect / Seed r 0.011598435 0.23319198 two-sided 0.85 1.00
#> 44 Slope / Seed r 0.077073974 1.63665889 two-sided 0.07 1.00
#> 45 Form / Seed F 5.561841954 0.50422249 greater 0.20 1.00
#> 46 PhysD / Seed r 0.078156305 1.37549602 two-sided 0.19 1.00
#> 47 ZoogD / Seed F 3.369068338 1.27476528 greater 0.12 1.00
#> 48 Snow / Seed r -0.177640721 -1.92068825 two-sided 0.05 1.00
#>
#> ---
#> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
plot(four.comb, stat = "G")
