Dear Kobby, Please post the output of sessionInfo() and class(result.md).
Best, Wolfgang >-----Original Message----- >From: K Amoatwi [mailto:amoatwi...@gmail.com] >Sent: Monday, 22 June, 2020 22:30 >To: Viechtbauer, Wolfgang (SP) >Cc: r-help@r-project.org >Subject: Re: [R] Error message in meta-analysis package Metafor-weights ="" > >Hi Wolfgang and All, >I am still practising my meta-analysis with the "Metafor" package, I tried >to run the code for "Forest plot" and got error message as shown below: >forest(result.md) >> forest(result.md) >Error in UseMethod("forest") : > no applicable method for 'forest' applied to an object of class >"c('rma.uni', 'rma')" > >Thank you in advance for your support > >regards >Kobby > >On Tue, Jun 16, 2020 at 12:50 PM Viechtbauer, Wolfgang (SP) ><wolfgang.viechtba...@maastrichtuniversity.nl> wrote: >Dear Amoatwi, > >This way of using the escalc() function has been deprecated. It might be >added back once there is actually any benefit from having this >functionality, but for years it just meant that I had to maintain two >different ways of doing the exact same thing without any additional >benefits. > >Best, >Wolfgang > >-- >Wolfgang Viechtbauer, Ph.D., Statistician | Department of Psychiatry and >Neuropsychology | Maastricht University | P.O. Box 616 (VIJV1) | 6200 MD >Maastricht, The Netherlands | +31 (43) 388-4170 | http://www.wvbauer.com > >>-----Original Message----- >>From: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of K Amoatwi >>Sent: Tuesday, 16 June, 2020 4:50 >>To: r-help@r-project.org >>Subject: [R] Error message in meta-analysis package Metafor-weights ="" >> >>Dear All, >>I am using the example from one of the tutorial about "Metafor" package and >>"escalc" function, to learn how this package can be applied to do >>meta-analysi; the code and the data is directly from the tutorials but >>"weights=freq" option in the escalc function is given me error message >>This is the code below: >> >>library(metafor) # Load package >>#####DATASET 1: BCG Vaccine Trials >>data(dat.bcg) # BCG meta-analytic dataset >> >>##Formula based Specification >>##That is, what if I have multiple rows per study, corresponding to >>difference treatment groups? >> >>library(reshape2) # Load package for data reshaping >> >>bcg.long <- melt(dat.bcg[, c("trial", "tpos", "tneg", "cpos", "cneg")], id >>= "trial") >>bcg.long$pos <- ifelse(bcg.long$var == "tpos" | bcg.long$var == "cpos", 1, >>0) >>bcg.long$group <- ifelse(bcg.long$var == "tpos" | bcg.long$var == "tneg", >>1, 0) >> >>##sample of the data, the first 6 rows >>head(bcg.long) >> trial variable value pos group >>1 1 tpos 4 1 1 >>2 2 tpos 6 1 1 >>3 3 tpos 3 1 1 >>4 4 tpos 62 1 1 >>5 5 tpos 33 1 1 >>6 6 tpos 180 1 1 >> >>##Now applying the " escalc " function >> >>escalc(factor(pos)~factor(group)| factor(trial),weights = value,data = >>bcg.long, measure = "OR") >> >>##Then I got this error message >>Error in escalc(factor(pos) ~ factor(group) | factor(trial), weights = >>value, : >> object 'value' not found >> >>I used the same data with different example from another author and got a >>similar error message >>Second code with the same data but different coding >>Sample data >> >>with the first 6 rows of the rearranged data shown below. (T=treatment, >>C=Control group, Out=outcome whether positive or negative, and then >>frequency) >> study grp out freq >>1 1 T + 4 >>2 1 T - 119 >>3 1 C + 11 >>4 1 C - 128 >>5 2 T + 6 >>6 2 T - 300 >> >>>escalc(out ~ grp | study, weights = freq, data = dat.fm, measure = "OR") >> >>Error in escalc(out ~ grp | study, weights = freq, data = dat.fm, measure = >>"OR") : >> object 'freq' not found >> >>I am not sure what I am doing wrong since both authors were able to get >>their results while I am getting error messages. >> >>Any help will be very much appreciated >> >>Amoatwi ______________________________________________ R-help@r-project.org 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.
