On 19 Oct 2017, at 7:44 am, P. Roberto Bakker <robertobakker at gmail.com> wrote:
Hi,
I understood from the metafor documentation you can either use vi
(variance) or sei (standard error (=sqrt of variance) in rma()..
However, with vi and I get other results than with sei. I would expect the
same results should be the same.
Can somebody help me understand this, or am I doing something wrong?
Tnx in advance,
Roberto
PS in the meta-analysis literature I read that se = sqrt of variance. But I
learned from statistics that SD = sqrt of variance. Can somebody explain me
this?
# A tibble: 10 ? 6
yi sei vi `inverse varience` `weighed hedge`
X__1
<dbl> <dbl> <dbl> <dbl> <dbl>
<dbl>
1 1.91498797 0.4231468 0.17905321 5.584932 10.6950776
1.91498797
2 -0.25848358 0.2615776 0.06842283 14.615005 -3.7777390
-0.25848358
3 0.06543005 0.3204569 0.10269263 9.737797 0.6371445
0.06543005
4 0.77363080 0.3290877 0.10829873 9.233718 7.1434890
0.77363080
5 -0.79554100 0.3341517 0.11165733 8.955973 -7.1248437
-0.79554100
6 0.29374938 0.2387312 0.05699258 17.546145 5.1541691
0.29374938
7 0.94409401 0.2527629 0.06388910 15.652122 14.7770750
0.94409401
8 -0.56731857 0.2423818 0.05874893 17.021588 -9.6566629
-0.56731857
9 0.18910949 0.1766278 0.03119739 32.053967 6.0617093
0.18910949
10 0.38103574 0.1713235 0.02935176 34.069510 12.9817010
0.38103574
WITH SEI
*> reis <- rma(measure="SMD", yi, sei, data=re, method="FE", digits=2)*
*> reis*
*Fixed-Effects Model (k = 10)*
*Test for Heterogeneity: *
*Q(df = 9) = 16.54, p-val = 0.06*
*Model Results:*
*estimate se zval pval ci.lb <http://ci.lb> ci.ub *
* 0.25 0.16 1.54 0.12 -0.07 0.56 *
*---*
*Signif. codes: 0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1 *
*WITH VI*
*> res <- rma(measure="SMD", yi, vi, data=re, method="FE", digits=2)>
resFixed-Effects Model (k = 10)Test for Heterogeneity: Q(df = 9) = 51.46,
p-val < .01Model Results:estimate se zval pval ci.lb <http://ci.lb>
ci.ub 0.22 0.08 2.88 <.01 0.07 0.38 **---Signif. codes: 0
?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1 *
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