meta analysis for sensitivity and specificity

classic Classic list List threaded Threaded
5 messages Options
Reply | Threaded
Open this post in threaded view
|

meta analysis for sensitivity and specificity

greg holly
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

        [[alternative HTML version deleted]]

______________________________________________
[hidden email] mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Reply | Threaded
Open this post in threaded view
|

Re: meta analysis for sensitivity and specificity

Michael Dewey-3
Dear Greg

I think you are going to need to supply more information. WHat do you
mean by "in SAS differently"? If you just want to do an analysis using
the Reitsma model then there are options in R of course.

https://CRAN.R-project.org/view=MetaAnalysis

for further questions may I suggest using the mailing list dedicated to
meta-analysis in R

https://stat.ethz.ch/mailman/listinfo/r-sig-meta-analysis//

Michael


On 06/12/2018 21:38, greg holly wrote:

> 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
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
> [hidden email] mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

--
Michael
http://www.dewey.myzen.co.uk/home.html

______________________________________________
[hidden email] mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Reply | Threaded
Open this post in threaded view
|

Re: meta analysis for sensitivity and specificity

Viechtbauer Wolfgang (SP)
In reply to this post by greg holly
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:[hidden email]] 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

______________________________________________
[hidden email] mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Reply | Threaded
Open this post in threaded view
|

Re: meta analysis for sensitivity and specificity

greg holly
Dear All;

I sincerely apologize for TYPOS. My question is that:

Does anyone know any R library that runs meta-analysis differently for
Sensitivity and Specificity if I have only the following info in my data
set?
Once again my apologies for the mistake in my earlier email.

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

On Fri, Dec 7, 2018 at 6:16 AM Viechtbauer, Wolfgang (SP) <
[hidden email]> 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:[hidden email]] 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
>

        [[alternative HTML version deleted]]

______________________________________________
[hidden email] mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Reply | Threaded
Open this post in threaded view
|

Re: meta analysis for sensitivity and specificity

greg holly
In reply to this post by Viechtbauer Wolfgang (SP)
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) <
[hidden email]> 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:[hidden email]] 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
>

        [[alternative HTML version deleted]]

______________________________________________
[hidden email] mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.