[R-meta] mismatch in outputs from meta-analysis and corresponding forest plot

[Joao Afonso]

Dear all,

I am conducting a meta-analysis and came across an odd issue. I ran the
model for assessing the moderator effect of a variable as per below.
















*subganal.lcmbi=rma(yi, vi, data=ies.logit.lcmbi, mods=~lcmbi,
method="DL")pes.logit.lcm=rma(yi, vi, data=ies.logit.lcmbi,
mods=~lcmbi=="Records", method="DL")pes.logit.records=rma(yi, vi,
data=ies.logit.lcmbi, mods=~lcmbi=="Locomotion Scoring Method",
method="DL")pes.subg.lcmbi=predict(subganal.lcmbi,transf=transf.ilogit)dat.samevar=data.frame(estimate=c((pes.logit.lcm$b)[1],
(pes.logit.records$b)[1]),stderror=c((pes.logit.lcm$se)[1],
(pes.logit.records$se)[1]),tau2=subganal.lcmbi$tau2)pes.logit.lcm=rma(estimate,
sei=stderror,method="DL",data=dat.samevar)pes.lcmbi=predict(pes.logit.lcm,
transf=transf.ilogit)print(pes.logit.lcm, digits=3) #display subgroup 1
summary effect sizeprint(pes.logit.records, digits=3) #display subgroup 2
summary effect sizeprint(subganal.lcmbi, digits=3) #display subgroup
analysis resultsprint(pes.lcmbi, digits=3) #display recomputed summary
effect size*

and got the following output


*  pred ci.lb <http://ci.lb/> ci.ub cr.lb <http://cr.lb/> cr.ub 0.237 0.149
0.355 0.112 0.434*

However when plotting the corresponding forest plot I get the pooled at
0.25 (0.21 - 0.31).
































*subganal.lcmbi=rma(yi, vi, data=ies.logit.lcmbi, mods=~lcmbi,
method="DL")pes.summary=metaprop(nlameanimal, ssizeanimal, author,
data=ies.logit.lcmbi,                     sm="PLO",
 method.tau="DL",                     method.ci <http://method.ci>="NAsm",
                   byvar=lcmbi,                     tau.common=TRUE,

 tau.preset=sqrt(subganal.lcmbi$tau2))precision=sqrt(ies.logit.lcmbi$vi)jpeg(file="forest_cow_all_lcmbi.jpeg",
width=11, height=12, units="in", res=300)forest(pes.summary,
 xlim=c(0,1),       pscale=1,       rightcols=FALSE,
 leftcols=c("studlab", "effect", "ci"),       leftlabs=c("Study",
"Prevalence", "95% C.I."),       text.random="Prevalence of Lameness in
British Dairy Cattle",       bylab = "Lameness Data Source",
 print.byvar = TRUE,       xlab="Prevalence of Lameness", smlab="",
 weight.study="random", squaresize=0.5, col.square="navy",
 col.diamond="maroon", col.diamond.lines="maroon",
 pooled.totals=FALSE,       comb.fixed=FALSE,       fs.hetstat=10,
 print.tau2=TRUE,       print.Q=TRUE,       print.pval.Q=TRUE,
 print.I2=TRUE,       digits=2,       sortvar = precision)dev.off()*

Any idea of what could be producing this or what could I be doing wrong?

Many thanks,

Joao


-- 
João Afonso
DVM, MSc Veterinary Epidemiology
PhD Student
Department of Infection and Global Health
University of Liverpool
+351914812305

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