Can anyone please tell me how to change the language interface so as to receive
error messages in English. Currently it's a mixed jargon of French an English.
Thank you for any help.
Anne
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R-help@r-proj
d it a range of powers and
find the one for which it calculates the sample size you had. There is a more
elegant way to do this using uniroot but brute force should work.
Michael
On 26/08/2019 13:42, Marc Schwartz via R-help wrote:
>
>> On Aug 26, 2019, at 6:24 AM, CHATTON An
Hello everybody,
I am trying to accommodate the R codes provided by Donohue for sample size
calculation in the package "longpower" with lmmpower function to estimate the
post-hoc power (asked by a reviewer) of a binary GEE model with a three-way
interaction (time x condition x continuous predic
Dear all,
Thank you for your remarks.
The data under analysis were multiply-imputed using Mice.
To compare the nested models, I used the following R codes by van Buuren:
pool.compare (Model2, Model1, method = c("wald"), data = NULL)
As far as I know the Wald statistic tests the null hypothesis that
Hello,
I am currently analysed two nested models using the same sample. Both the
simpler model (Model 1 ~ x1 + x2) and the more complex model (Model 2 ~ x1 + x2
+ x3 + x4) yield the same adjusted R-square. Yet the p-value associated with
the deviance statistic is highly significant (p=0.0047),
Dear all,
I am having problems in obtaining standardized betas on a multiply-imputed data
set. Here are the codes I used :
imp = mice(data, 5, maxit=10, seed=42, print=FALSE)
FitImp <- with(imp,lm(y ~ x1 + x2 + x3))
Up to here everything is fine. But when I ask for the standardized coefficients
Hi R folks,
In my previous post I forgot to mention that I was new to R. I was really
grateful for your quick help. I have two further questions:
1) In the graph of a regression line I would like to show one specific residual
yi obs - yi pred (let's take the person whose residual is 76). How do I
chner
-
Am 18.04.2018 um 15:26 schrieb CHATTON Anne via R-help:
> Hello,
>
> I am trying to graph a regression line using the followings:
>
> Age <- c(39, 47, 45, 47, 65, 46, 67, 42, 67, 56, 64, 56, 59, 34, 42,
> 48, 45,
Hello,
I am trying to graph a regression line using the followings:
Age <- c(39, 47, 45, 47, 65, 46, 67, 42, 67, 56, 64, 56, 59, 34, 42, 48, 45,
17, 20, 19, 36, 50, 39, 21, 44, 53, 63, 29, 25, 69)
BloodPressure <- c(144, 220, 138, 145, 162, 142, 170, 124, 158, 154, 162,
150, 140, 110, 128, 130, 1
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