[R] Conditional wald statistics in ASRemlR

[Sue Lewis]

Hi, I'm running a model in ASRemlR and the conditional wald statistics table
is producing groupings for the marginality of some variables (A's B's and
C's in the tables below) that we are struggling to understand. From our
understanding of the model we are fitting and the reference manual, we were
expecting main effects to be grouped together (e.g Maring "A") and the two
way interactions to be grouped together (e.g. Margin "B") and to be marginal
with respect to main effects and then the three-way interactions to be
grouped together (e.g. Margin "C") and to be marginal with respect to
two-way interactions and main effects. However, this doesn't seem to be
happening. For example, the main effect of yr (year - of which there are 2
and is a factor) appears to be given Margin "C",which groups it with a
number of 2-way interactions and the three-way interactions in terms of
marginality. Does anyone have any suggestions as to why is this the case?

I have been told that ASReml has a general algorithm for determining the
groupings which is not fool proof.  Stand-alone ASReml allows you to
redefine the groupings.  What we would like to know is whether those
capabilities exist for the R version, and if not, are there other ways we
can set up the model to get the terms in the appropriate grouping.

 

Thanks so much for any suggestions,

Sue

 

> W1<-wald.asreml(m1.asreml, ssType="conditional")

 

  asreml 3.0 (15 April 2013), Library: 3.0hj (15 November 2011), X86_64

     LogLik         S2      DF      wall     cpu

   -50111.3907      0.0010 51482  09:02:03    15.9

 

> W1$Wald$p<-round(1-pf(W1$Wald[,2], W1$Wald[,1], 90),3)

> W1

$Wald

                                Df           F.inc
F.con                     Margin    p

(Intercept)         1              1772.0000            585100.0
0.000

yr                             1             7.6790                   9030.0
C             0.007

months                5              9.1350                   10790.0
A            0.000

dayc                       1              21.9900                 19780.0
B             0.000

haschicks             1              38.0200                 50740.0
B             0.000

chickagec             1              6.5720                   14020.0
B             0.012

bsc                         1               191.3000             192600.0
B             0.000

sex                          1             0.7405                   742.4
A             0.392

winspc                   1             45.7700                  44840.0
A             0.000

sinwinc                 1              3.4120                   2586.0
A             0.068

rainc                      1              16.4300                 15910.0
A             0.000

months:dayc         5          15.2400                 14320.0
C             0.000

months:sex          5            5.3200                   669.1
B             0.000

haschicks:sex       1           7.7330                   8906.0
C             0.007

chickagec:sex       1           0.2351                   288.6
C             0.629

bsc:sex                  1             1.9470                   1726.0
C             0.166

sex:winspc          1             23.1700                 19900.0
B             0.000

sex:sinwinc         1             12.4700                 5766.0
B             0.001

sex:rainc               1             0.7769                   625.3
B             0.380

months:sex:winspc  10    2.7480                 2258.0                   C
0.005

months:sex:sinwinc 10    2.6850                 1834.0                   C
0.006

months:sex:rainc   10    1.7060                   1706.0                   C
0.091

 

 

 

 

 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Sue Lewis

NERC fellow

Institute of Evolutionary Biology

School of Biological Sciences

University of Edinburgh

Edinburgh, EH9 3JT, UK

 

Email: sue.lewis at ed.ac.uk

Tel: +44 (0)131 6505444

http://lewis.bio.ed.ac.uk <http://lewis.bio.ed.ac.uk/> 

 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

 

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