On 10/10/2013 08:35 AM, Rebecca Stirnemann wrote:
Dear R wizards,

Though I hate to do it after weeks of my code not working I need some help
since I cant find an example which seems to work.
I am trying to create a graph which show the probability of predation of a
nest on one side (either 1 to 0) or (0% to 100%) on one side
and grass height at the bottom. I want to then add my predicted lines from
my glmr onto the graph for three habitat types.

I would like to repeat this procedure 3 times for three different grass
heights 25- 50- 100 to see the effect size.

My data:
    landusenumb landuse sitename rat ground.cover_lo  1  plantation
far.leftroad_LHS 0 60  1 plantation far.leftroad_LHS 1 70  1 plantation
far.leftroad_LHS 1 10  1 plantation far.leftroad_LHS 1 30  1 plantation
far.leftroad_LHS 1 50  1 plantation far.leftroad_LHS 0 20  1 plantation
far.leftroad_LHS 0 70  1 plantation far.leftroad_LHS 0 100  1 plantation
far.leftroad_LHS 0 90

#Graph


#Fit model

mod1<- glmer(frat ~ flandusenumb + ground.cover_lo + (1|fsite) ,family =
binomial, data= mao1)


#Calculate predicted values

newdata1<- data.frame(ground.cover_lo = seq(0,10,length=100), flandusenumb
= rep(1,2,3))

pred34<- predict(mod1,newdata=newdata1,type="response")



#Plot model predicted curves

plot(c(0,100),c(0,1),type="n",xlab="grasscover",ylab="Probability of
predation")

lines(newdata1$frat,pred34,lwd=3,col="blue")


Hi Rebecca,
First, your sample data are a bit mangled, and should look like this:

mao1
landusenumb landuse    sitename rat ground.cover_lo
1           plantation far.leftroad_LHS   0      60
1           plantation far.leftroad_LHS   1      70
1           plantation far.leftroad_LHS   1      10
1           plantation far.leftroad_LHS   1      30
1           plantation far.leftroad_LHS   1      50
1           plantation far.leftroad_LHS   0      20
1           plantation far.leftroad_LHS   0      70
1           plantation far.leftroad_LHS   0     100
1           plantation far.leftroad_LHS   0      90

If you want the predicted values with ground cover as above, then:

ground.cover_lo = c(25,50,100)

The variable names in the first model don't match those in the data frame, but I assume these were typos. What does "pred34" look like? This will tell you what function you should be using to plot it.

Jim

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