On 10/10/2013 11:33 PM, Rebecca Stirnemann wrote:
> Hi Michael,
> Thanks! That worked. Which is so brilliant!
> A couple of questions. In regards to display.
> Do you know how to add labels on to the graph? The code below doesn't
> work.
Not surprising, since your data, mao1, is not in the lme4 package, and
you didn't provide it.
> Also is it possible some how to add all three lines onto one graph and
> some how tell it to display things without colours?
For the example I gave you, multiline=TRUE will plot all curves in a
single graph.
You have to learn how to read the help pages to find answers to such
questions.
plot(Effect(c("recipe", "temperature"), fm1), colors=rep("black",3),
multiline=TRUE)
# put the legend inside the plot
plot(Effect(c("recipe", "temperature"), fm1), colors=rep("black",3),
multiline=TRUE, key.args=list(x=.10, y=.80))
>
> Thanks soooooo much!
> Rebecca
>
> library(effects)
>
> ?effect
>
>
> library(lme4)
>
> data(mao1,package="lme4")
>
> fm1<-glm(frat~flandusenumb+ ground.cover_lo+(1|fsite),mao1,
>
> REML=FALSE)
>
> plot(effect("frat:ground.cover_lo",fm1, xlab="Low ground cover (%) ",
>
> ylab="Proportion of nests predated",),grid=TRUE)
>
> plot(Effect(c("flandusenumb","ground.cover_lo"),fm1))# equivalent
>
>
>
>
> On Fri, Oct 11, 2013 at 1:41 AM, Michael Friendly <frien...@yorku.ca
> <mailto:frien...@yorku.ca>> wrote:
>
> Perhaps you are looking for the effects package, which can plot
> effects
> (predicted values) for terms in mer objects from lme4?
>
> library(effects)
> ?effect
>
> library(lme4)
> data(cake, package="lme4")
> fm1 <- lmer(angle ~ recipe * temperature + (1|recipe:replicate), cake,
> REML = FALSE)
> plot(effect("recipe:temperature", fm1), grid=TRUE)
> plot(Effect(c("recipe", "temperature"), fm1)) # equivalent
>
>
>
> On 10/10/2013 12:52 AM, Rebecca Stirnemann wrote:
>
> Thanks Jim for helping,
>
> Your sample data actually looks like my dataset. The one I put
> up looks
> strange for some reason so please ignore that.
> I have three landusenumb variables 1 2 and 3. is rep (1,2,3)
> correct?
>
> When I run the following code I am getting:
>
> mod1 <- glmer(frat ~ flandusenumb + ground.cover_lo +
> (1|fsite) ,family =
>
> binomial, data= mao1)
>
>
> #Calculate predicted values
> newdata1 <- data.frame(ground.cover_lo = c(25,50,100),
> flandusenumb =
>
> rep(1,2,3))
>
> pred34 <- predict(mod1,newdata=newdata1,type="response")
>
>
> Error in UseMethod("predict") :
> no applicable method for 'predict' applied to an object of
> class "mer"
>
> Can you see what I am doing wrong?
> What I am aiming for is a graph which looks like this.
>
> Thanks
> Rebecca
>
>
>
>
>
>
> On Thu, Oct 10, 2013 at 5:33 PM, Jim Lemon <j...@bitwrit.com.au
> <mailto:j...@bitwrit.com.au>> wrote:
>
> 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
>
>
>
>
>
>
> --
> Michael Friendly Email: friendly AT yorku DOT ca
> Professor, Psychology Dept. & Chair, Quantitative Methods
> York University Voice: 416 736-2100 x66249
> <tel:416%20736-2100%20x66249> Fax: 416 736-5814 <tel:416%20736-5814>
> 4700 Keele Street Web: http://www.datavis.ca
> Toronto, ONT M3J 1P3 CANADA
>
>
>
>
> --
> www.samoanbirds.com <http://www.samoanbirds.com>
--
Michael Friendly Email: friendly AT yorku DOT ca
Professor, Psychology Dept. & Chair, Quantitative Methods
York University Voice: 416 736-2100 x66249 Fax: 416 736-5814
4700 Keele Street Web: http://www.datavis.ca
Toronto, ONT M3J 1P3 CANADA
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