cvar: Create a contextual variable for regression

In gmonette/yscs: Collection of tools used in York University's Statistical Consulting Service

Description

cvar and dvar are designed to be used in regression formulas to create a contextual mean of a cluster-varying variable and a 'centered-within-groups' version.

Usage

cvar(x, id, ...)

Arguments

x	variable to be centered or residualized within groups. If x is a factor, cvar and dvar return matrices whose columns are named consistently with the names of coding variables for factors.
id	identifies clusters

Examples

## Not run: 
dd <- data.frame(x= 1:100, id = rep( LETTERS[1:10], each = 10))
dd$a <- factor(sample( c('a','b','c'), 100, replace = T))
dd$y <- dd$x + rep(rnorm(10), each = 10) + rnorm(100) + as.numeric(dd$a)
library(nlme)
fit <- lme( y ~ x + cvar(x,id), dd, random = ~ 1 + dvar(x,id) | id)
anova( fit , type = 'm')
# The output of 'anova' can be used to test whether a contextual variable
# should be included in the model

## End(Not run)

gmonette/yscs documentation built on May 17, 2019, 7:28 a.m.