nested model and post hoc?
I rather suspect the problem is primarily statistical, not R related. If at all possible, try to get some local statistical advice. Most probably, you have empty cells in some of the dpi.f by diss.f table. Also, using a Gaussian family and the cells/mg response may be inappropriate: 1 cell in 5 mg is different than 100 cells in 500 mg. This obviously depends on your data, which is why local help might be important. Cheers, Bert
On Wednesday, August 5, 2015, a_wohl <sithlord1 at gmx.net> wrote:
Hi :-) i am really looking forward to get some help... Since I am a
R-beginner I need it.
I have a model consisting of the factors: dpi, infection, dissection day
and
plate. My reskponse variable is cells/mg. dpi is nested in dissection day.
They are all fixed variables.
I produced this nested model (best AIC index)
glm.3<-cm.2~infect.f+dpi.f+dpi.f/diss.f, na.action=na.omit)
summary(glm.3)
Call:
glm(formula = cm.2 ~ infect.f + dpi.f + dpi.f %in% diss.f, family =
gaussian,
na.action = na.omit)
Deviance Residuals:
Min 1Q Median 3Q Max
-2.7746 -0.3625 0.0080 0.3628 1.9031
Coefficients: (18 not defined because of singularities)
Estimate Std. Error t value Pr(>|t|)
(Intercept) 7.01887 0.15278 45.941 < 2e-16 ***
infect.finf 0.05544 0.08107 0.684 0.4946
infect.fsha -0.15563 0.08831 -1.762 0.0791 .
dpi.f2 0.08924 0.20459 0.436 0.6630
dpi.f4 -0.40167 0.21082 -1.905 0.0577 .
dpi.f8 0.01961 0.20789 0.094 0.9249
dpi.f16 0.82210 0.20469 4.016 7.54e-05 ***
dpi.f32 0.99639 0.21435 4.648 5.09e-06 ***
dpi.f1:diss.f2 0.13276 0.21077 0.630 0.5293
dpi.f2:diss.f2 NA NA NA NA
dpi.f4:diss.f2 0.46749 0.20784 2.249 0.0253 *
dpi.f8:diss.f2 -0.06555 0.20205 -0.324 0.7459
dpi.f16:diss.f2 NA NA NA NA
dpi.f32:diss.f2 NA NA NA NA
dpi.f1:diss.f3 NA NA NA NA
dpi.f2:diss.f3 -0.15794 0.20186 -0.782 0.4346
dpi.f4:diss.f3 0.20921 0.21081 0.992 0.3218
dpi.f8:diss.f3 NA NA NA NA
dpi.f16:diss.f3 -0.03611 0.20178 -0.179 0.8581
dpi.f32:diss.f3 NA NA NA NA
dpi.f1:diss.f4 0.14040 0.20459 0.686 0.4931
dpi.f2:diss.f4 -0.01701 0.21152 -0.080 0.9360
dpi.f4:diss.f4 NA NA NA NA
dpi.f8:diss.f4 NA NA NA NA
dpi.f16:diss.f4 -0.19082 0.20168 -0.946 0.3449
dpi.f32:diss.f4 NA NA NA NA
dpi.f1:diss.f5 NA NA NA NA
dpi.f2:diss.f5 NA NA NA NA
........and so forth.
Since i decided for a nested modul, I wonder where the NAs are coming from?
Since I want to perform a post hoc test, I was trysing the glht fuinction
form the multcomp package.
I always get this error
Error in modelparm.default(model, ...) :
dimensions of coefficients and covariance matrix don't match
I think this is due to my NAs in the summary(glm.3).
Can anyone help me, how I can perform a post hoc test (Bonferroni) on my
data?
thank you
a_wohl
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