I was wondering if anyone could help me with this, simple problem.
I am essentially following the example on Hadley's webpage
(http://had.co.nz/ggplot2/geom_errorbar.html), but it still doesn't make any
sense to me.
df <- data.frame(trt = factor(c("intact", "intact", "removed", "removed")),
So here is some information that I hope gets criticized by the
higher-intelligences that posted on this topic. Beware that I'm not a
statistician and I'm just saying about what I think is correct.
First, before fitting any model, check the distribution of your data, in
some cases a simple anova i
Could someone or Richard explain to me what he meant by
"This also shows a singular Error(). We look at the data and see that
plot is identical to the three-way veget:fruit:block interaction."
It seems to me that I just needed to recoded the plots, in order to get rid
of the Error message. If t
When we ran a regular ANOVA we showed that both mice and raccoons respond
positively to cover. So we decided to use raccoons as a co-variate because
those are mouse predators and their presence per se could explain part of
the variation on mice activity. That is the reason why I'm running this
AN
What does the command
c:\progra~1\R\R-2.9.1\bin\Rgui --vanilla
do?
At first I thought that I could run it from R. But then it did not work.
I'm using a mac, and I don't know how access MSDOS in a mac. I actually
installed R on the pc and tried to run the command from MSDOS and it also
didn't wor
I can actually run the code from my post.
I used the nabble for my list server
http://www.nabble.com/ANCOVA-with-defined-error-terms-td25055311.html#a25100032
I don't know which server you use, but that one is not truncated, I can copy
the code just fine and run it.
Anyway, here it is again
summ
Hi Richard, there are no empty cells.
I transform everything into factor, except the co-variate coon.
Here is the full analysis with dput of the data.
I'm afraid I have not enough DF for the thre-way interaction using your
model as well. 12 plots divided in 3 blocks, each plot assigned to 2 cros
Thank you Richard, this works. But, the model you suggested me lacks some
between subjects interactions, namely:
veget:time:block
fruit:time:block.
According to Sokal and Rohlf I need to report those as well.
Also, any ideas why the sum of squares on my model are different from yours
summar
Thanks Richard,
I tried running the analysis the way you suggested but here is the error
that I get
> track.aov <- aov(mice ~ coon+block*veget*fruit*time -
> block:veget:fruit:time
+ + Error(block/plot), data = track)
Warning message:
In aov(kotz.mice ~ kotz.coon + block * veget
I am trying to run an ANCOVA with defined error terms. Thus I have to use
AOV and not lm.
my response variable is proportion of mice paw prints on track plates. These
plates were placed on plots that had vegetation and fruit manipulated to two
levels each (present or absent), and were sampled mo
I am using AOV and I am not sure if my model structure is correct for the
repeated measures.
I want to verify if there is a interaction of a random factor(block) with
fixed factors(veget,fruit, time,)
> model<-aov(trackarcsin~veget*fruit*time*block
> +Error(block/(veget*fruit)),data=mice)
Becau
That works. I still think you should have named RESHAPE as "MAGIC"! It is
amazing how much of time saver this tool is!
Thanks a lot.
--
View this message in context:
http://www.nabble.com/RESHAPE-package-question.-tp18792801p18794249.html
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imple but I just don't know how to do it. I was hoping that
it would give me the following data
t1 t2 t3 t4 M F id
1 1 0 0 0 2 1 1
2 1 0 1 1 3 1 1
Many thanks!
hpdutra wrote:
>
> Hi there,
>
> I am trying to reorganized my data sets so that it is easy for M
Hi there,
I am trying to reorganized my data sets so that it is easy for MARK to read
it.
Basically I have the encounter histories of 1837 butterflies
The data looks like this the first 4 columns are the occasions and the last
two code for male and female
> t1 t2 t3 t4 M F
> 10 0
er that,
so I need to get the groupedData correct.
Thank you very much
Humberto Dutra
try
trap$time<-factor(trap$time)
trap$block<-factor(trap$block)
On 7/19/08, hpdutra <[EMAIL PROTECTED]> wrote:
>
>
> Hi everyone. I am trying to add a formula to my data using the
>
Hi everyone. I am trying to add a formula to my data using the groupedData
function.
My experiment consists of randomized block design using fruits, vegetation
and time as factors. The idea is to see if fruits, vegetation and time
explain the abundance of mice. I am using tree density as a covar
have you tried reshape package?
library(reshape)
dfm <- melt(dataframe, m = "date")
You can find out more about reshape at http://had.co.nz/reshape
sprohl wrote:
>
> Hello,
> I have to merge several serie by "date". I used:
>
> cb<-merge(cbds,cbbond,by=c("date"),all=T).
>
> I have the dail
apparently he does
https://stat.ethz.ch/pipermail/r-packages/2007/000298.html
Felipe Carrillo wrote:
>
> Hi (Hadley): Do you still have the ggplot2 book being published this
> summer?
>
> Felipe D. Carrillo Fishery Biologist Department of the Interior US
> Fish & Wildlife Service Califor
I am trying to fit a formula to my data, but I just can't find the right way
to do it.
My experiment consists of manipulating FRUITS and VEGETATION to two levels
each(intact or removed) on 12 experimental plots.
This leaves me with 4 treatment combinations
Fruit intact Vegetation removed
Fruit in
First I would like to say thank you for taking the time to read it.Here is my
problem.
I am running a lmer analysis for binary longitudinal (repeated measures)
data.
Basically, I manipulated fruits and vegetation to two levels each(present
and absent) and I am trying to access how these factors
In fact I am using Crawley example to fit my data.
I am running a lmer analysis for binary longitudinal (repeated measures)
data.
Basically, I have 12 plots, divided in 3 blocks, each block contain 4 plots.
Plots were manipulate for fruits (F) and vegetation (V) that were either
intact(I) or re
Sounds like a repeated measures design, if so then you have to incorporate
this into your model before interpreting the results.
Brooke LaFlamme-2 wrote:
>
> Hi, I am trying to do a repeated measures ANOVA to determine if there is a
> significant difference between two sets of timecourse data.
I am trying to do an exercise on Crawley's book and I get this error message. I
ran the same analysis in the past but now that I upgraded my R in my Macbook I
get this message. Is this a bug or what is going on.
It doesn't make any sense
> library(MASS)
> attach(bacteria)
> table(y)
y
n y
43
> library(MASS)
> attach(bacteria)
> table(y)
y
n y
43 177
> y<-1*(y=="y")
> table(y,trt)
trt
y placebo drug drug+
0 12 1813
1 84 4449
> library(lme4)
> model1<-lmer(y~trt+(week|ID),family=binomial,method="PQL")
Error in match.arg(method, c("Laplace", "AGQ"))
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