Thank you Peter!
Great solutions! That's exactly what I was looking for.
Maurício Cardeal
Em 08/04/2017 09:11, peter dalgaard escreveu:
> Here's one way:
>
>> ddw <- reshape(dd, direction="wide", idvar="pair", timevar="treatfac")
>> names(ddw)
> [1] "pair" "imprfac.A" "imprfac.B"
>> xtabs(
Change to the desired directory before starting R.
--
Sent from my phone. Please excuse my brevity.
On April 8, 2017 10:40:13 AM PDT, Da Zheng wrote:
>Hello,
>
>By default, the home directory of R is "/usr/lib/R" in Ubuntu.
>Everything works fine.
>
>However, when I installed Jupyter notebook an
Hello,
By default, the home directory of R is "/usr/lib/R" in Ubuntu.
Everything works fine.
However, when I installed Jupyter notebook and the R kernel with
anaconda2, it seems the R home directory is changed to some directory
in anaconda2. This messes up compilation and linking. I wonder how I
On 2017/4/7 23:13, Jeff Newmiller wrote:
I think it is a fundamental characteristic of graphics drivers that output will
look different in the details... you are on a wild goose chase. Postscript in
particular has a huge advantage in font presentation over other graphics output
mechanisms.
On 2017/4/7 23:13, Jeff Newmiller wrote:
I think it is a fundamental characteristic of graphics drivers that output will
look different in the details... you are on a wild goose chase. Postscript in
particular has a huge advantage in font presentation over other graphics output
mechanisms.
Dear Dr. Eichner and Dr. Kohl,
First, thank you for your response. I tried your code and R it worked
perfectly I just had to add: mi.t.test(implist*$imputation,* "pre_test",
"post_test", alternative = "greater", paired = TRUE, var.equal = TRUE,
conf.level = 0.95) for the code to run.
Thank you ve
Would be grateful for advice on gam/bam model selection incorporating random
effects and autoregressive terms.
I have a multivariate time series recorded on ~500 subjects at ~100 time
points. One of the variables (A) is the dependent and four others (B to E) are
predictors. My basic formula i
Here's one way:
> ddw <- reshape(dd, direction="wide", idvar="pair", timevar="treatfac")
> names(ddw)
[1] "pair" "imprfac.A" "imprfac.B"
> xtabs(~ imprfac.A + imprfac.B, ddw)
imprfac.B
imprfac.A + -
+ 1 3
- 2 1
(reshape() is a bit of a pain to wrap one's mind around;
Hi!
Is it possible to automatically construct a table like this:
#treat B
# improvement
# + -
#treat A improvement + 1 3
# - 2 1
From these data:
pair <- c(1,1,2,2,3,3,4,4,5,5,6,6,
Hi Joe,
I have read your question with great interest. I am a little bit astonished to
read about your project. There is a big national institute in Germany called
GESIS
(https://de.wikipedia.org/wiki/GESIS_%E2%80%93_Leibniz-Institut_f%C3%BCr_Sozialwissenschaften)
which does the same job you a
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