[R-meta] Help with meta-analisys of variation
Fernando Klitzke Borszcz
|ern@ndobor@zcz @end|ng |rom gm@||@com
Mon Jul 22 19:22:20 CEST 2019
Dear Professor Wolfgang,
Thank you for your help.
Best wishes
Em qui, 18 de jul de 2019 às 09:50, Viechtbauer, Wolfgang (SP) <
wolfgang.viechtbauer using maastrichtuniversity.nl> escreveu:
> The covariance between two lnSD values depends on the correlation between
> the two variables (for which you computed the lnSD values) and can be
> estimated with:
>
> r^2 / (2*(n-1))
>
> where r is the correlation between the two variables. So, you need to know
> the correlation between the measurements at different stages in order to
> compute the covariances.
>
> Best,
> Wolfgang
>
> -----Original Message-----
> From: Fernando Klitzke Borszcz [mailto:fernandoborszcz using gmail.com]
> Sent: Thursday, 18 July, 2019 14:35
> To: Viechtbauer, Wolfgang (SP)
> Cc: r-sig-meta-analysis using r-project.org
> Subject: Re: [R-meta] Help with meta-analisys of variation
>
> Dear Professor Wolfgang,
>
> Thank you for your response.
>
> My question is if I should use any value of correlation to determine the
> variance-covariance matrix in this type of data? I am not sure if I could
> use a correlation value, because the variances of log-transformed standard
> deviations (lnSD) are based only on sample size.
>
> Below an example of my data.
>
> study yi vi exercise stage
> 1 A 2.351 0.0250 row 3
> 2 A 2.351 0.0250 row 4
> 3 A 2.261 0.0250 row 5
> 4 A 1.922 0.0250 row 7
> 5 A 1.887 0.0250 row 10
> 6 B 1.884 0.0313 cycle 3
> 7 B 1.851 0.0313 cycle 4
> 8 B 1.774 0.0313 cycle 7
> 9 B 1.740 0.0313 cycle 10
> 10 C 1.831 0.0278 cycle 3
> 11 D 1.732 0.0294 run 5
>
> Em qui, 18 de jul de 2019 às 07:26, Viechtbauer, Wolfgang (SP) <
> wolfgang.viechtbauer using maastrichtuniversity.nl> escreveu:
> Dear Fernando,
>
> I am not sure I fully understand your question. My interpretation of your
> question/problem is as follows. You have studies that measure some property
> of interest in a group of a subjects at multiple timepoints. And for each
> timepoint, you compute ln(SD) with sampling variance 1/(2*(n-1)). But since
> multiple ln(SD) values are based on the same sample of subjects, you want
> to compute the covariance between those ln(SD) values and you are not sure
> how to do that. Is this the essence of your question?
>
> Best,
> Wolfgang
>
> -----Original Message-----
> From: R-sig-meta-analysis [mailto:
> r-sig-meta-analysis-bounces using r-project.org] On Behalf Of Fernando Klitzke
> Borszcz
> Sent: Thursday, 11 July, 2019 15:42
> To: r-sig-meta-analysis using r-project.org
> Subject: [R-meta] Help with meta-analisys of variation
>
> Hi all,
>
> I am conducting a meta-analysis about standard deviations of change between
> 2 conditions in the metafor package. I am using effect sizes (lnSD) and
> their sampling variance, based on Nakagawa et al. (
>
> https://besjournals.onlinelibrary.wiley.com/doi/full/10.1111/2041-210X.12309
> ).
> However, many studies included in my analysis, the same subject produces
> multiple results (multiple time points). Thus, I should determine the
> variance-covariance matrix of the effects. However, I am not sure if it is
> appropriate to determine the variance-covariance matrix using any
> correlation value for this type of effect, because effects variances are
> based only on the sample size (1/2[n-1]). Is there any alternative to
> determine the variance-covariance matrix for this type of data, or I should
> just include the study as a random effect?
>
> Best wishes!
>
> Att.
> Fernando Borszcz
>
> --
> Att.
> Fernando Klitzke Borszcz
> Doutorando em Educação Física
> Laboratório de Esforço Físico - LAEF
> Centro de Desportos - CDS
> Universidade Federal de Santa Catarina- UFSC
> (48) 998261406
> http://lattes.cnpq.br/4442928023267586
> orcid.org/0000-0002-3773-6906
>
--
Att.
Fernando Klitzke Borszcz
Doutorando em Educação Física
Laboratório de Esforço Físico - LAEF
Centro de Desportos - CDS
Universidade Federal de Santa Catarina- UFSC
(48) 998261406
http://lattes.cnpq.br/4442928023267586
[image: ORCID iD icon]orcid.org/0000-0002-3773-6906
<https://orcid.org/0000-0002-3773-6906>
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