contr.meandif: Mean difference contrast matrix

In RoBMA: Robust Bayesian Meta-Analyses

Mean difference contrast matrix

Description

Return a matrix of mean difference contrasts. This is an adjustment to the contr.orthonormal that ascertains that the prior distributions on difference between the gran mean and factor level are identical independent of the number of factor levels (which does not hold for the orthonormal contrast). Furthermore, the contrast is re-scaled so the specified prior distribution exactly corresponds to the prior distribution on difference between each factor level and the grand mean – this is approximately twice the scale of contr.orthonormal.

Usage

contr.meandif(n, contrasts = TRUE)

Arguments

n	a vector of levels for a factor, or the number of levels
contrasts	logical indicating whether contrasts should be computed

Value

A matrix with n rows and k columns, with k = n - 1 if contrasts = TRUE and k = n if contrasts = FALSE.

References

\insertAllCited

Examples

contr.meandif(c(1, 2))
contr.meandif(c(1, 2, 3))

RoBMA documentation built on July 26, 2023, 5:13 p.m.