[R] meta analysis for sensitivity and specificity

[greg holly]

Hi Viechtbauer and Micheal;


Thanks so much for writing. It is much appreciated.

Regards,
Greg

On Fri, Dec 7, 2018 at 6:16 AM Viechtbauer, Wolfgang (SP) <
wolfgang.viechtbauer using maastrichtuniversity.nl> wrote:

> Dear Greg,
>
> I am not sure if I understand your question. If you are asking how to do
> this in R, then one could use the metafor or meta package for this. The
> specificity and sensitivity values are proportions, so one would usually
> meta-analyze them after a logit transformation. But all of the specificity
> values are equal to 1, so this is pretty pointless. For sensitivity:
>
> dat <- data.frame(pi = c(.66, .55, .76, .40, .46), ni = c(57, 33, 17, 30,
> 11))
> dat$xi <- round(dat$pi * dat$ni)
>
> library(metafor)
>
> dat <- escalc(measure="PLO", xi=xi, ni=ni, data=dat)
> res <- rma(yi, vi, data=dat)
> res
> predict(res, transf=transf.ilogit)
>
> One could also use a logistic mixed-effects model for this:
>
> res <- rma.glmm(measure="PLO", xi=xi, ni=ni, data=dat)
> res
> predict(res, transf=transf.ilogit)
>
> If you want to analyze the specificity and sensitivity together, then you
> would want to use a bivariate model. There are some specific packages for
> this. See the Meta-Analysis Task View (
> https://cran.r-project.org/web/views/MetaAnalysis.html). I just saw that
> Michael also replied with the same suggestion (and the note about the
> mailing list).
>
> Best,
> Wolfgang
>
> >-----Original Message-----
> >From: R-help [mailto:r-help-bounces using r-project.org] On Behalf Of greg
> >holly
> >Sent: Thursday, 06 December, 2018 22:38
> >To: r-help mailing list
> >Subject: [R] meta analysis for sensitivity and specificity
> >
> >Does anyone know any R library that runs meta-analysis in SAS differently
> >for  Sensitivity and Specificity if I have only the following info?
> >
> >Regards,
> >
> >Greg
> >
> >specificity sample_size Sensitivity Sample_size
> >1 21 0.66 57
> >1 70 0.55 33
> >1 19 0.76 17
> >1 10 0.4 30
> >1 16 0.46 11
>

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