# cvar: Create a contextual variable for regression In gmonette/WWCa: Tools for poststratification

## 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

 ``` 1 2 3 4 5 6 7 8 9 10 11 12``` ```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)

• `factor`: factor method for cvar

• `default`: default methods for cvar

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11``` ```## 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.