Does anyone have suggestions for reporting a robust ANCOVA?

I'm following the example in Andy Field's R book where he suggests that after failing the test for homogeneity of regression slopes, one might do a robust ANCOVA ala Wilcox 2005. I'm able to run the tests no problem, and interpreting them is also not an issue, but for output of the following nature (see below), does anyone know of a standard way to report this data?

I think a way to start at least will be to report the standard ANCOVA up to the point where the interaction is significant and then say robust procedures were followed, how to report these though are a bit beyond me.

ancova(covGrp1, dvGrp1, covGrp2, dvGrp2)
[1] "NOTE: Confidence intervals are adjusted to control the probability"
[1] "of at least one Type I error."
[1] "But p-values are not"
$output
X n1 n2 DIF TEST se ci.low ci.hi p.value crit.val
[1,] 10.30 20 12 -22.166667 2.7863062 7.955575 -47.42320 3.089867 0.0213100575 3.174696
[2,] 11.30 28 17 -19.184343 2.7536447 6.966891 -39.98396 1.615273 0.0167914292 2.985495
[3,] 12.45 32 23 -20.350000 3.9162704 5.196270 -35.02758 -5.672423 0.0008787346 2.824637
[4,] 14.00 27 34 -8.314171 1.4638404 5.679698 -23.71193 7.083583 0.1524122220 2.711016
[5,] 16.10 14 17 3.431818 0.3796813 9.038682 -22.28197 29.145604 0.7085490133 2.844860

ancboot(covGrp1, dvGrp1, covGrp2, dvGrp2,tr = .2, nboot=2000)
[1] "Note: confidence intervals are adjusted to control FWE"
[1] "But p-values are not adjusted to control FWE"
[1] "Taking bootstrap samples. Please wait."
$output
X n1 n2 DIF TEST ci.low ci.hi p.value
[1,] 10.30 20 12 -22.166667 -2.7863062 -47.00379 2.670459 0.0355
[2,] 11.30 28 17 -19.184343 -2.7536447 -40.93482 2.566135 0.0185
[3,] 12.45 32 23 -20.350000 -3.9162704 -36.57264 -4.127360 0.0015
[4,] 14.00 27 34 -8.314171 -1.4638404 -26.04606 9.417719 0.1525
[5,] 16.10 14 17 3.431818 0.3796813 -24.78674 31.650380 0.6980