add_grouping: Create a grouping factor

Description

A new factor G can be defined having levels based on those of an existing factor A. This adds G to the reference grid and redefines A as being nested in G.

Usage

add_grouping(object, newname, refname, newlevs)

Arguments

object

A ref.grid object

newname

Character name of the grouping factor to be created

refname

Character name of an existing factor in object whose levels are to be grouped

newlevs

Character vector or factor of the same length as the levels for refname. Each element specifies the corresponding level for newname

Value

A ref.grid object with the factor newname added. It will include a nesting structure such that refname is nested in newname, and with newname added to any existing nesting that involves refname.

Details

This function is useful when one wants to group certain levels of some treatment factor together and summarize by those groups -- without fitting a new model. For example, suppose a factor hosp refers to five hospitals. A call like newgrid <- add_grouping(refgrid, "envir", "hosp", c("rural", "urban", "urban", "rural", "urban")) would add a two-level grouping factor named envir in which the first and fourth hospitals are rural and the others are urban. Subsequently, we may use lsmeans(newgrid, "envir") to obtain the marginal means for the rural and urban environments.

If newlevs is specified as a factor, the user can use its levels attribute to control the order in which levels are presented. Otherwise, it will be alphabetical.

Examples

Run this code

# NOT RUN {
require("lsmeans")

fiber.lm <- lm(strength ~ diameter + machine, data = fiber)
frg <- ref.grid(fiber.lm)

## Suppose the machines are of two types
gfrg <- add_grouping(frg, newname = "type", refname = "machine", 
                     newlevs = c("computerized", "computerized", "manual"))
gfrg

lsmeans(gfrg, "type", contr = "pairwise")

# }