[R-meta] Handling dependencies among multiple independent and dependent variables

[Viechtbauer Wolfgang (SP)]

Glad you found that page -- I would have direct you there anyway.

How many parameters are you actually trying to estimate?

Best,
Wolfgang

-----Original Message-----
From: Jens Schüler [mailto:jens.schueler at wiwi.uni-kl.de] 
Sent: Tuesday, 03 April, 2018 3:45
To: Viechtbauer Wolfgang (SP); r-sig-meta-analysis at r-project.org
Subject: AW: Handling dependencies among multiple independent and dependent variables

Nevermind, I just went through your info on speeding up model fitting: 
http://www.metafor-project.org/doku.php/tips:speeding_up_model_fitting

Even though I am using an AMD R5 processor with 6 physical cores, I decided
to give the MKL avenue a shot and well, it cranked the CPU usage up from
about 7% to 55% - hopefully this speeds things up.

Best
Jens

-----Ursprüngliche Nachricht-----
Von: R-sig-meta-analysis <r-sig-meta-analysis-bounces at r-project.org> Im
Auftrag von Jens Schüler
Gesendet: Montag, 2. April 2018 22:17
An: Viechtbauer Wolfgang (SP)
<wolfgang.viechtbauer at maastrichtuniversity.nl>;
r-sig-meta-analysis at r-project.org
Betreff: Re: [R-meta] Handling dependencies among multiple independent and
dependent variables

Hi Wolfgang,

after rearranging my coding sheet, the rmat function worked like a charm (of
course I screwed up here and there before I got it right).
However, currently I am wondering about the computational performance of
matrix calculations in R.

My data consists of ~ 1700 observations drawn from 422 samples and the
rma.mv function is currently up and running for over 5 hours.
I use the latest base version of R, together with R Studio, and have a
potent CPU in my desktop - of which R only uses about 7%.
Thus, are the calculations really that lengthy/tedious or is it more likely
that I still screwed something up?

Best
Jens