dosresmeta (version 2.0.1)

blup.dosresmeta: Best Linear Unbiased Predictions from dosresmeta Models

Description

This method function computes (empirical) best linear unbiased predictions from fitted dose-response meta-analytical models represented in objects of class "dosresemta".

Usage

# S3 method for dosresmeta
blup(object, ...)

Arguments

object

objects of classe "dosresmeta".

…

further arguments passed to or from other methods.

Details

The method function blup produces (empirical) best linear unbiased predictions from dosresmeta objects. Predictions are expressed in terms of study-specific deviations as random effects. Predicted random effects from blup are a shrunk version of study-specific realizations, where study-specific predictions borrow strength from the assumption of an underlying distribution in a (usually hypothetical) population of studies. Blup are not avaialable for fixed-effects models since the are meaningless in that context.

Examples

# NOT RUN {
## Load data and run the linear and quadratic models
data("alcohol_cvd")
lin <- dosresmeta(formula = logrr ~ dose, type = type, id = id,
                  se = se, cases = cases, n = n, data = alcohol_cvd) 
quadr <- dosresmeta(formula = logrr ~ dose + I(dose^2), type = type, id = id,
                    se = se, cases = cases, n = n, data = alcohol_cvd) 

## blup prediction for the previous models
blup(lin)
blup(quadr)

# }