ANOVA type lll ss table for GLMER?
On 14-05-14 10:02 AM, Henrik Singmann wrote:
Dear Heather,
you could try to use mixed from the afex package which will give you
Type III p-values for the effects via Chi^2 tests (or alternatively via
parametric bootstrap):
require(afex)
(spden2 <- mixed(SpDens~(treat*samp)-1+(1|TRANSECT),family=poisson,
data=rm, nAGQ = 9, method = "LRT")
Note however, that loading afex changes your overall contrasts, to reset
the default contrasts use:
options(contrasts=c('contr.treatment', 'contr.poly'))
But (despite the fact that I **really** don't like afex's default behaviour of changing the overall contrasts) -- you should definitely use contr.sum when computing a marginal ANOVA table (i.e. do NOT reset the contrasts until after you're done constructing your table), if you insist on doing that.
Furthermore, (g)lmer doesn't break the factors done by *all* levels. It removes the first levels (usually). Hence the parameters cannot directly be interpreted if this level is "significant". Hope this helps, Henrik Am 14.05.2014 15:45, schrieb Heather Moylett:
Hello group,
This is my first time posting, so I hope I have explained my needs
clearly
below.
I am running a repeated measure analysis with a raw species count data
set
(SpDens). I have run different model types (zeroinfl, glm, glmer) and
have
identified glmer to have the best fit. The output generated by GLMER
breaks
my between groups (treat) and within groups (samp) factors down by
levels.
In addition to this, I would like to look at the effect of treat and samp
overall, something similar to an ANOVA table (Type lll SS). When I use
Anova(object) I receive an ANOVA table with an F val and no P-vals. I
would
prefer to stick with the z-stat and p-vals. I have seen this reported in
other papers, so I know it can be done...just can't figure out how to
do it!
Components of the model:
samp: 23 sampling dates is the repeated measure (within groups)
treat: 4 levels (between groups)
TRANSECT: experimental unit (subject), 4/treat and data collected from
all
16 every sampling date
When I run this code:
RM <- read.csv("C:/Users/heatbell/Desktop/Walthour-Moss/STATS/CH
1/Final/R/RM.csv")
View(RM)
rm <- subset(RM, SAMPLE >= 2)
rm<- within(rm, {
samp<-factor(SAMPLE)
yr<-factor(YEAR)
treat<-factor(TREAT)
})
summary(rm)
summary(spden<-glmer(SpDens~(treat*samp)-1+(1|TRANSECT),family=poisson,
data=rm, nAGQ = 9))
Thank you for the help!
Heather