# [R] Help with simulation of unbalanced clustered data

Chao Liu p@ych@o||u @end|ng |rom gm@||@com
Thu Dec 17 19:07:14 CET 2020

```Thank you for your help Abby!

On Wed, Dec 16, 2020 at 11:32 PM Abby Spurdle <spurdle.a using gmail.com> wrote:

> Hi Chao Liu,
>
> I'm having difficulty following your question, and examples.
> And also, I don't see the motivation for increasing, then decreasing
> the sample sizes.
> Intuitively, one would compute the correct sample sizes, first time
> round...
>
> But I thought I'd add some comments, just in case they're useful.
>
> If the problem relates to memberships (in clusters), then the problem
> can be simplified.
> All one needs is an integer vector, where each value is the index of
> the cluster.
>
> To compute random memberships of 600 observations in 20 clusters, one
> could run:
>
>     m <- sample (1:20, 600, TRUE)
>
> To compute the number of observations per cluster, one could then run:
>
>     table (m)
>
> In the above code, the probability of an observation being assigned to
> each cluster, is uniform.
> Non-uniform sampling can be achieved by supplying a 4th argument to
> the sample function, which is a numeric vector of weights.
>
>
> On Wed, Dec 16, 2020 at 10:08 PM Chao Liu <psychaoliu using gmail.com> wrote:
> >
> > Dear R experts,
> >
> > I want to simulate some unbalanced clustered data. The number of clusters
> > is 20 and the average number of observations is 30. However, I would like
> > to create an unbalanced clustered data per cluster where there are 10%
> more
> > observations than specified (i.e., 33 rather than 30). I then want to
> > randomly exclude an appropriate number of observations (i.e., 60) to
> arrive
> > at the specified average number of observations per cluster (i.e., 30).
> The
> > probability of excluding an observation within each cluster was not
> uniform
> > (i.e., some clusters had no cases removed and others had more excluded).
> > Therefore in the end I still have 600 observations in total. How to
> realize
> > that in R? Thank you for your help!
> >
> > Best,
> >
> > Liu
> >
> >         [[alternative HTML version deleted]]
> >
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