Hi Erika,
As mentioned, I haven't run the model before and I don't have access
to your data set, so you might want to post your reply to the list as well
(cc'd again).
As another guessing-without-trying-anything, I'd first make sure
that in fact pop and family are factor variables with the same length as
a,b,c,treat,centroidsize.
Also having not used glmer before, I'm not sure how to get the p
values...since estimates and std. errors and t-values are reported, the df's
are likely known and so they probably exist in the "model" object you
created. Of course, your highest t-value is 1.92, so none of your fixed
effects would be significant at the .05 level (the two-tailed z-score cutoff
is 1.93, which is the limit for t).
--Adam
On Wed, 10 Sep 2008, Erika Crispo wrote:
Thanks! I am still having some problems. I have tried the following:
model=glmer(cbind(a,b,c)~pop*treat+centroidsize+(1|pop/family))
Error: Matrices must have same number of columns in rbind2(..1, r)
In addition: Warning messages:
1: In family:pop :
numerical expression has 104 elements: only the first used
2: In family:pop :
numerical expression has 104 elements: only the first used
I don't get the error messages if I exclude the nesting (i.e. exclude pop on
the RHS). But even then, I don't know how to interpret the output. How can I
get P values for pop and treat? I've attached my data file.
summary(model)
Linear mixed model fit by REML
Formula: cbind(a, b, c) ~ pop * treat + centroidsize + (1 | family)
AIC BIC logLik deviance REMLdev
-685.3 -656.2 353.6 -822.8 -707.3
Random effects:
Groups Name Variance Std.Dev.
family (Intercept) 9.8877e-13 9.9437e-07
Residual 2.3502e-05 4.8478e-03
Number of obs: 104, groups: family, 28
Fixed effects:
Estimate Std. Error t value
(Intercept) 4.518e-03 4.329e-03 1.0438
popkah -2.338e-03 1.902e-03 -1.2297
popkant -2.328e-03 1.881e-03 -1.2380
poprwe -3.728e-03 1.941e-03 -1.9204
treatn -8.703e-04 1.957e-03 -0.4448
centroidsize -1.886e-06 2.464e-06 -0.7656
popkah:treatn 3.440e-03 2.695e-03 1.2765
popkant:treatn 1.198e-03 2.699e-03 0.4439
poprwe:treatn 4.662e-03 2.746e-03 1.6976
Correlation of Fixed Effects:
(Intr) popkah popknt poprwe treatn cntdsz ppkh:t ppknt:
popkah -0.228
popkant -0.335 0.507
poprwe -0.193 0.490 0.492
treatn -0.092 0.485 0.476 0.479
centroidsize -0.951 0.009 0.119 -0.023 -0.128
popkah:trtn 0.121 -0.705 -0.352 -0.346 -0.719 0.036
popknt:trtn 0.095 -0.352 -0.680 -0.347 -0.721 0.063 0.520
poprwe:trtn 0.117 -0.346 -0.346 -0.707 -0.706 0.037 0.510 0.511
<>< <>< <>< <>< <>< <>< <><
Erika Crispo, PhD candidate
McGill University, Department of Biology
http://www.biology.mcgill.ca/grad/erika/index.htm
<> ><> ><> ><> ><> ><> ><>
----- Original Message ----- From: "Adam D. I. Kramer"
<[EMAIL PROTECTED]>
To: "Erika Crispo" <[EMAIL PROTECTED]>
Cc: <r-help@r-project.org>
Sent: Wednesday, September 10, 2008 5:47 PM
Subject: Re: [R] mixed model MANCOVA
Hi Erika,
I have not tried this before, and I hope that somebody will correct
me if I'm wrong, but the glmer function in the lme4 library appears to do
what you want. From examples(lmer):
lmer> (gm1 <- glmer(cbind(incidence, size - incidence) ~ period + (1 |
herd), family = binomial, data = cbpp))
...I guess that this will do what you want it to because it has multiple
variables on the LHS and both continuous and categorical variables on the
RHS, along with an explicit grouping structure.
In your case, you probably want to leave the family= argument out, as noted
in ?glmer, "If 'family' is missing then a linear mixed model is fit;
otherwise a generalized linear mixed model is fit." ...MANCOVA tend to be
generalized linear models.
Once again, though, I have not used this system personally, haven't seen
your data, and don't know what output to expect. Hopefully somebody else
can
confirm or deny this solution's efficacy.
--Adam
On Mon, 8 Sep 2008, Erika Crispo wrote:
Hello,
I need to perform a mixed-model (with nesting) MANCOVA, using Type III
sums of squares. I know how to perform each of these types of tests
individually, but I am not sure if performing a mixed-model MANCOVA is
possible. Please let me know.
Erika
<>< <>< <>< <>< <>< <>< <><
Erika Crispo, PhD candidate
McGill University, Department of Biology
http://www.biology.mcgill.ca/grad/erika/index.htm
<> ><> ><> ><> ><> ><> ><>
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