[R-meta] Performance of metafor::vcalc() vs clubSandwich::impute_covariance_matrix()

[James Pustejovsky]

Hi Tamar,

The difference in compute time is because of a difference in how the
default output of these functions is structured.
clubSandwich::impute_covariance_matrix() returns a block-diagonal by
default. metafor::vcalc() returns a full (dense) matrix by default. Say
that you have J studies and study j has kj effect sizes. The block-diagonal
matrix has sum(kj^2) entries, whereas the full matrix has sum(kj)^2
entries. If J is large and the kjs are mostly small, this can make for a
really big difference in object size. However, setting the option
vcalc(sparse = TRUE) will return a block-diagonal matrix and should lead to
performance comparable to impute_covariance_matrix().

Regarding your second question, I'm not sure what might be going on. Could
you provide a reproducible example?

James

On Tue, Aug 6, 2024 at 8:20 AM Tamar Novetsky via R-sig-meta-analysis <
r-sig-meta-analysis using r-project.org> wrote:

> Hello,
>
> I am working on a script to run multiple meta-regressions on different
> subsets of the same dataset, and have been
> using clubSandwich::impute_covariance_matrix() to generate the
> variance-covariance matrix necessary as an input to metafor::rma.mv().
> However, I recently learned that impute_covariance_matrix() has been
> superseded by metafor::vcalc(), so I have been working to replace my usage
> of the former function with the latter. In that process, I discovered that
> vcalc() seems to be much slower than impute_covariance_matrix() - about
> 150x slower in one use case that I benchmarked using the microbenchmark
> package. Since I will be running this many times in a loop, performance
> matters quite a lot to me in this context.
>
> Can anyone help me understand why vcalc() would be so much slower? Is it
> possible that I'm using it incorrectly?
>
> Secondly/possibly relatedly, I found that the results from vcalc() are
> always either exactly the same or exactly double the results from
> impute_covariance_matrix(). Does anyone have a sense of why that would be?
> Could that be related to the performance differences?
>
> Thanks so much for your help,
>
>
> *Tamar Novetsky* *(she/her)*
> Data Scientist I
> Eastern Time Zone
>
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