# NOT RUN {
### REPRODUCE THE RESULTS IN JACKSON ET AL. (2013)
# INSPECT THE DATA
hyp
# INPUT THE CORRELATION (CAN ALSO BE INPUTTED DIRECTLY, SEE BELOW)
(S <- inputcov(hyp[c("sbp_se","dbp_se")],cor=hyp$rho))
# CHECK WITH THE FIRST STUDY
cov2cor(xpndMat(S[1,]))
# META-ANALYSIS, REML MODEL
model <- mvmeta(cbind(sbp,dbp),S=S,data=hyp)
print(summary(model),digits=2)
round(model$Psi,2)
# META-ANALYSIS, REML MODEL (INPUTTING THE CORRELATION DIRECTLY)
model <- mvmeta(cbind(sbp,dbp),S=cbind(sbp_se,dbp_se)^2,data=hyp,
control=list(Scor=hyp$rho))
print(summary(model),digits=2)
# META-ANALYSIS, MM MODEL
model <- mvmeta(cbind(sbp,dbp),S=S,data=hyp,method="mm")
print(summary(model),digits=2)
round(model$Psi,2)
# META-REGRESSION, REML MODEL
model <- mvmeta(cbind(sbp,dbp)~ish,S=S,data=hyp)
print(summary(model),digits=2)
# META-REGRESSION, MM MODEL
model <- mvmeta(cbind(sbp,dbp)~ish,S=S,data=hyp,method="mm")
print(summary(model),digits=2)
# }
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