cvar: Create a contextual variable for regression

Description Usage Arguments Methods (by class) Examples

View source: R/capply.R

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

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cvar(x, id, all, na.rm, ...)

## S3 method for class 'factor'
cvar(x, id, all = FALSE, na.rm = TRUE, ...)

## Default S3 method:
cvar(x, id, all, na.rm = TRUE, ...)

dvar(x, id, all, na.rm, ...)

## Default S3 method:
dvar(x, id, all, na.rm = TRUE, ...)

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

all

(default FALSE) if TRUE cvar.factor returns the columns means of an incidence matrix including the first level. Otherwise, the first level is dropped for use in a linear model.

na.rm

(default TRUE) whether to drop missing values

Methods (by class)

Examples

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## 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/WWCa documentation built on May 14, 2017, 12:59 p.m.