Learn R Programming

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

Run this code
# 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)

# }

Run the code above in your browser using DataLab