Dear Boris,
Great !!!! But what about Mark in your R code ? Don't we have to precise in the
R code that mark ranges between 1 to 6 (1 ; 1.5 ; 2 ; 2.5 ; 3 ; 3.5 ; 4 ; 4.5 ;
5 ; 5.5 ; 6) ?
By the way, to fit a linear mixed model, I use lme4 package and then the lmer
function works with the variables like in this example here below :
library(lme4)
mm=lmer(Mark ~Gender + (1 | School / Class), data=Dataset)
With your R code, how can I write the lmer function to make it work ?
Best,
S.
Le dimanche 19 mai 2019 à 15:26:39 UTC+2, Boris Steipe
<boris.ste...@utoronto.ca> a écrit :
Fair enough - there are additional assumptions needed, which I make as follows:
- each class has the same size
- each teacher teaches the same number of classes
- the number of boys and girls is random within a class
- there are 60% girls (just for illustration that it does not have to be
equal)
To make the dependencies explicit, I define them so, and in a way that they
can't be inconsistent.
nS <- 10 # Schools
nTpS <- 5 # Teachers per School
nCpT <- 2 # Classes per teacher
nPpC <- 20 # Pupils per class
nS * nTpS * nCpT * nPpC == 2000 # Validate
mySim <- data.frame(School = paste0("s", rep(1:nS, each = nTpS*nCpT*nPpC)),
Teacher = paste0("t", rep(1:(nTpS*nS), each = nCpT*nPpC)),
Class = paste0("c", rep(1:(nCpT*nTpS*nS), each = nPpC)),
Gender = sample(c("boy", "girl"),
(nS*nTpS*nCpT*nPpC),
prob = c(0.4, 0.6),
replace = TRUE),
Mark = numeric(nS*nTpS*nCpT*nPpC),
stringsAsFactors = FALSE)
Then you fill mySim$Mark with values from your linear mixed model ...
mySim$Mark[i] <- simMarks(mySim[i]) # ... or something equivalent.
All good?
Cheers,
Boris
> On 2019-05-19, at 08:05, varin sacha <varinsa...@yahoo.fr> wrote:
>
> Many thanks to all of you for your responses.
>
> So, I will try to be clearer with a larger example. Te end of my mail is the
> more important to understand what I am trying to do. I am trying to simulate
> data to fit a linear mixed model (nested not crossed). More precisely, I
> would love to get at the end of the process, a table (.txt) with columns and
> rows. Column 1 and Rows will be the 2000 pupils and the columns the different
> variables : Column 2 = classes ; Column 3 = teachers, Column 4 = schools ;
> Column 5 = gender (boy or girl) ; Column 6 = mark in Frecnh
>
> Pupils are nested in classes, classes are nested in schools. The teacher are
> part of the process.
>
> I want to simulate a dataset with n=2000 pupils, 100 classes, 50 teachers and
> 10 schools.
> - Pupils n°1 to pupils n°2000 (p1, p2, p3, p4, ..., p2000)
> - Classes n°1 to classes n°100 (c1, c2, c3, c4,..., c100)
> - Teachers n°1 to teacher n°50 ( t1, t2, t3, t4, ..., t50)
> - Schools n°1 to chool n°10 (s1, s2, s3, s4, ..., s10)
>
> The nested structure is as followed :
>
> -- School 1 with teacher 1 to teacher 5 (t1, t2, t3, t4 and t5) with classes
> 1 to classes 10 (c1, c2, c3, c4, c5, c6, c7, c8,c9,c10), pupils n°1 to pupils
> n°200 (p1, p2, p3, p4,..., p200).
>
> -- School 2 with teacher 6 to teacher 10, with classes 11 to classes 20,
> pupils n°201 to pupils n°400
>
> -- and so on
>
> The table (.txt) I would love to get at the end is the following :
>
> Class Teacher School gender Mark
> 1 c1 t1 s1 boy 5
> 2 c1 t1 s1 boy 5.5
> 3 c1 t1 s1 girl 4.5
> 4 c1 t1 s1 girl 6
> 5 c1 t1 s1 boy 3.5
> 6 ... .... .... ..... .....
>
>
> The first 20 rows with c1, with t1, with s1, gender (randomly slected) and
> mark (andomly selected) from 1 to 6
> The rows 21 to 40 with c2 with t1 with s1
> The rows 41 to 60 with c3 with t2 with s1
> The rows 61 to 80 with c4 with t2 with s1
> The rows 81 to 100 with c5 with t3 with s1
> The rows 101 to 120 with c6 with t3 with s1
> The rows 121 to 140 with c7 with t4 with s1
> The rows 141 to 160 with c8 with t4 with s1
> The rows 161 to 180 with c9 with t5 with s1
> The rows 181 to 200 with c10 with t5 with s1
>
> The rows 201 to 220 with c11 with t6 with s2
> The rows 221 to 240 with c12 with t6 with s2
>
> And so on...
>
> Is it possible to do that ? Or am I dreaming ?
>
>
> Le dimanche 19 mai 2019 à 10:45:43 UTC+2, Linus Chen <linus.l.c...@gmail.com>
> a écrit :
>
>
>
>
>
> Dear varin sacha,
>
> I think it will help us help you, if you give a clearer description of
> what exactly you want.
>
> I assume the situation is that you know what a data structure you
> want, but do not know
> how to conveniently create such structure.
> And that is where others can help you.
> So, please, describe the wanted data structure more thoroughly,
> ideally with example.
>
> Thanks,
> Lei
>
> On Sat, May 18, 2019 at 10:04 PM varin sacha via R-help
> <r-help@r-project.org> wrote:
>>
>> Dear Boris,
>>
>> Yes, top-down, no problem. Many thanks, but in your code did you not forget
>> "teacher" ? As a reminder teacher has to be nested with classes. I mean the
>> 50 pupils belonging to C1 must be with (teacher 1) T1, the 50 pupils
>> belonging to C2 with T2, the 50 pupils belonging to C3 with T3 and so on.
>>
>> Best,
>>
>>
>> Le samedi 18 mai 2019 à 16:52:48 UTC+2, Boris Steipe
>> <boris.ste...@utoronto.ca> a écrit :
>>
>>
>>
>>
>>
>> Can you build your data top-down?
>>
>>
>>
>> schools <- paste("s", 1:6, sep="")
>>
>> classes <- character()
>> for (school in schools) {
>> classes <- c(classes, paste(school, paste("c", 1:5, sep=""), sep = "."))
>> }
>>
>> pupils <- character()
>> for (class in classes) {
>> pupils <- c(pupils, paste(class, paste("p", 1:10, sep=""), sep = "."))
>> }
>>
>>
>>
>> B.
>>
>>
>>
>>> On 2019-05-18, at 09:57, varin sacha via R-help <r-help@r-project.org>
>>> wrote:
>>>
>>> Dear R-Experts,
>>>
>>> In a data simulation, I would like a balanced distribution with a nested
>>> structure for classroom and teacher (not for school). I mean 50 pupils
>>> belonging to C1, 50 other pupils belonging to C2, 50 other pupils belonging
>>> to C3 and so on. Then I want the 50 pupils belonging to C1 with T1, the 50
>>> pupils belonging to C2 with T2, the 50 pupils belonging to C3 with T3 and
>>> so on. The school don’t have to be nested, I just want a balanced
>>> distribution, I mean 60 pupils in S1, 60 other pupils in S2 and so on.
>>> Here below the reproducible example.
>>> Many thanks for your help.
>>>
>>> ##############
>>> set.seed(123)
>>> # Génération aléatoire des colonnes
>>> pupils<-1:300
>>> classroom<-sample(c("C1","C2","C3","C4","C5","C6"),300,replace=T)
>>> teacher<-sample(c("T1","T2","T3","T4","T5","T6"),300,replace=T)
>>> school<-sample(c("S1","S2","S3","S4","S5"),300,replace=T)
>>
>>> ##############
>>>
>>> ______________________________________________
>>> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>>> and provide commented, minimal, self-contained, reproducible code.
>
>>
>> ______________________________________________
>> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
______________________________________________
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
