write.cor: Adds correlation between time-course relative effects

In MBNMAtime: Run Time-Course Model-Based Network Meta-Analysis (MBNMA) Models

Adds correlation between time-course relative effects

Description

This uses a Wishart prior as default for modelling the correlation

Usage

write.cor(model, fun, omega = NULL, class.effect = list())

Arguments

model	A character object of JAGS MBNMA model code
fun	An object of class "timefun" generated (see Details) using any of tloglin(), tpoly(), titp(), temax(), tfpoly(), tspline() or tuser()
omega	DEPRECATED IN VERSION 0.2.3 ONWARDS (~uniform(-1,1) now used for correlation between parameters rather than a Wishart prior). A scale matrix for the inverse-Wishart prior for the covariance matrix used to model the correlation between time-course parameters (see Details for time-course functions). omega must be a symmetric positive definite matrix with dimensions equal to the number of time-course parameters modelled using relative effects (pool="rel"). If left as NULL (the default) a diagonal matrix with elements equal to 1 is used.
class.effect	A list of named strings that determines which time-course parameters to model with a class effect and what that effect should be ("common" or "random"). For example: list(emax="common", et50="random").

MBNMAtime documentation built on Oct. 14, 2023, 5:08 p.m.