[R-meta] [R meta] How to print z score for subgroup analysis
Michael Dewey
||@t@ @end|ng |rom dewey@myzen@co@uk
Mon May 20 10:38:30 CEST 2019
Dear Cath
It is not quite clear what you want here. When you say z score do you
mean a z test for the subgroup differences? Since you have three groups
the test is a chi squared and is labelled Q in the output (13.58 with 2 df).
Michael
On 19/05/2019 23:05, Cath Kids wrote:
> Dear all,
>
> I have conducted a subgroup analysis using meta in R.
> I used the following command but can't seem to find the z score in the
> output.
>
>> post_cb2_es.subgroup<-update.meta(post_cb2_es,
> + byvar=category,
> + comb.random = TRUE,
> + comb.fixed = FALSE,
> + print.zval = TRUE)
>
> Could anyone please kindly advise? Thanks a lot!!!
>
> Regards,
> Joanne
>
> ============Analysis results========================
>
> Number of studies combined: k = 18
>
> SMD 95%-CI t p-value
> Random effects model 0.2441 [ 0.0203; 0.4678] 2.30 0.0343
> Prediction interval [-0.5915; 1.0797]
>
> Quantifying heterogeneity:
> tau^2 = 0.1441; H = 1.67 [1.30; 2.15]; I^2 = 64.1% [40.6%; 78.3%]
>
> Quantifying residual heterogeneity:
> H = 1.20 [1.00; 1.62]; I^2 = 30.2% [0.0%; 61.8%]
>
> Test of heterogeneity:
> Q d.f. p-value
> 47.38 17 0.0001
>
> Results for subgroups (random effects model):
> k SMD 95%-CI Q tau^2 I^2
> category = CBM-A on IB 5 -0.1253 [-0.4858; 0.2351] 4.47 0.0465 10.5%
> category = CBM-I on AB 7 0.1314 [-0.1120; 0.3747] 6.46 0.0306 7.1%
> category = CBM-I on MB 6 0.6715 [ 0.2258; 1.1171] 10.58 0.1173 52.7%
>
> Test for subgroup differences (random effects model):
> Q d.f. p-value
> Between groups 13.58 2 0.0011
>
> Details on meta-analytical method:
> - Inverse variance method
> - Sidik-Jonkman estimator for tau^2
> - Hartung-Knapp adjustment for random effects model
>
> [[alternative HTML version deleted]]
>
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--
Michael
http://www.dewey.myzen.co.uk/home.html
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