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
meta analysis for sensitivity and specificity
5 messages · Michael Dewey, Wolfgang Viechtbauer, greg holly
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]]
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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 at 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
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) <
wolfgang.viechtbauer at 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 at 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
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 at 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 at 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