Hi All,
The data set that I have is a cluster data, and I want to run a HLM mixed
model with multi-level response. Here is my data set:
response:
- Level (num: 1, 2, 3, 4, 5 - 5 levels)
Covariates:
- Type (Factor: A, B, C - 3 levels)
- yr (num: 2006, 2007, ...)
- Male (num: 0=not
Hi,
Does anyone know if Ordinal package can be used for continuous covariate. In
CLMM function, can independent variables be continuous variables?
I used all dummy variable as the independent variables, the CLMM function
works, but when I added continuous variables in the model, it gave an
Hi:
I want to give an index with all the dates between Sept. to Nov. as 1, and
anything else is 0. It doesn't matter which year it is, as long as it is
between Sept. to Nov, then set up to 1, otherwise is 0.
My data frame looks like below:
ID Date
201 1/1/05 6:07 AM
201 3/27/09
I think I got it, I post it here see if you have better way, please let me
know.
index - rep(0, length(mydata[,1]))
index[as.Date(mydata3$Date) as.Date(2006-11-30 23:29:29 PM)
as.Date(mydata3$Date) as.Date(2006-09-01 00:00:00 AM)] - 1
index[as.Date(mydata3$Date) as.Date(2007-11-30 23:29:29
Hi,
I am trying to find the min of day for each student in each year.
Here is the dataset:
date studentid year
1/1/05 6:07 AM 236 20082009
3/27/09 9:45 AM 236 20082009
4/29/09 8:44 AM 236 20082009
Phil,
Thanks a lot, it works well.
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I've tried this on 2 different PCs now. I'm trying to run more than one R
script w/o closing and restarting JGR. In other words, if I run one script
which uses the PerformanceAnalytics package and subsequently attempt to run
another script, using a package such as lattice, then JGR crashes on
Hi Silvano:
Could you tell me what correlation=corSymm(form = ~ 1 |id) represents? In
our case, team is random effect, trt, pairs, grade, school are fixed effect,
and each team is within school.
I still got the different results from both SAS and R.
unstruct -
Hi
I am trying to convert SAS codes to R, but some of the result are quite
different from SAS.
When I ran proc mixed, I have an option ddfm=bw followed by the model. How
can I show this method in R (I am thinking that this maybe the reason that I
can't get the similar results)
below is my SAS
Hi Harold:
Yes, this was the R code that I tried, and got different result from SAS.
Is that mean I cannot actually use R to run unstructured covariance matrix?
How can I solve this problem if I need an unstructured covariance matrix
method?
Thanks for the help.
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Hi Harold:
I know the outputs are different between SAS and R, but the results that I
got have big difference.
Here is part of the result based on the SAS code I provided earlier:
Cov Parm SubjectEstimate Error
Value Pr Z
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