## Worked example of dosresmeta package 
## Data source
## Qin Liu  et al A two-stage hierarchical regression model for meta-analysis of 
## epidemiologic nonlinear dose-response data. Table 2. Summary of the studies 
## on the relation between alcohol intake and vascular disease risk.

library("dosresmeta")

alcohol_cvd <- read.table("http://alessiocrippa.altervista.org/data/alcohol_cvd.txt")

## Linear trend
lin <- dosresmeta(formula = logrr ~ dose, type = type, id = id,
            se = se, cases = cases, n = n, data = alcohol_cvd)
summary(lin)
predict(lin, delta = 5)


## Non-linearity (spline) using random-effect
library("rms")
knots <- quantile(alcohol_cvd$dose, c(.1, .5, .9))
spl <- dosresmeta(formula = logrr ~ rcs(dose, knots), type = type, id = id,
            se = se, cases = cases, n = n, data = alcohol_cvd)
summary(spl)

## Tabulate result
pred <- predict(spl, data.frame(dose = seq(0, 60, 2.5)))
print(pred, digits = 2)

## Graphical prediction
newdata = data.frame(dose = seq(0, 60, .5))
with(predict(spl, newdata),{
  plot(get("rcs(dose, knots)dose"), pred, type = "l", log = "y", ylab = "Relative risk", las = 1,
       xlab = "Alcohol intake, grams/day", ylim = c(.4, 2), bty = "l")
  lines(get("rcs(dose, knots)dose"), ci.lb, lty = "dashed")
  lines(get("rcs(dose, knots)dose"), ci.ub, lty = "dashed")
})
rug(alcohol_cvd$dose, quiet = T)