[R-meta] see how much each study contributes to heterogenicity

[Dr. Gerta Rücker]

Dear Martin,


Produce a forest plot by


mi <- metainf(m)

forest(mi)


At the bottom of this plot, you find the usual random effect estimate 
(including information from all studies). If there were no heterogeneity 
at all, all confidence intervals (CI) would show the same pooled effect 
estimate. However, if you see a CI deviating from the others, then this 
apparently means that *omitting* this study changes the pooled estimate. 
This means that this study has a large influence on the pooled estimate 
when including all studies.


For example, use


data(Olkin1995)

m <- metabin(ev.exp, n.exp, ev.cont, n.cont, data = Olkin1995)

forest(m)
mi <- metainf(m)
forest(mi)


Studies 37 and 60 deviate from the rest. Comparing this to the first 
forest plot, you find that these are the largest studies and thus drive 
the pooled estimate.


Best,

Gerta


Am 13.10.2021 um 22:00 schrieb Martin Lobo:
> Hi every one,
> as I can see if any of the studies particularly influenced the high 
> level of heterogeneity. I did the sensitivity analysis with meteinf 
> but I don't know how to find this point.
> Thank you
>
>
>
> */
> /*
> */Lorenzo Mart�n Lobo /**/^MTSAC, FACC, FESC /*
> /*Especialista Jerarquizado�en Cardiolog�a*/
> /*/*Jefe de Dpto Enf. Cardiovasculares y Cardiometabolismo Hospital 
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> /
> /
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> /
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> /
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> de la SAC*/
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> Cardiovascular de la SAC*/
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>
-- 

Dr. rer. nat. Gerta R�cker, Dipl.-Math.

Guest Scientist
Institute of Medical Biometry and Statistics,
Faculty of Medicine and Medical Center - University of Freiburg

Zinkmattenstr. 6a, D-79108 Freiburg, Germany

Mail:     ruecker using imbi.uni-freiburg.de
Homepage: https://www.uniklinik-freiburg.de/imbi-en/employees.html?imbiuser=ruecker


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