emmobj {emmeans}R Documentation

Construct an emmGrid object from scratch

Description

This allows the user to incorporate results obtained by some analysis into an emmGrid object, enabling the use of emmGrid methods to perform related follow-up analyses.

Usage

emmobj(bhat, V, levels, linfct, df = NA, dffun, dfargs = list(),
  post.beta = matrix(NA), ...)

Arguments

bhat

Numeric. Vector of regression coefficients

V

Square matrix. Covariance matrix of bhat

levels

Named list or vector. Levels of factor(s) that define the estimates defined by linfct. If not a list, we assume one factor named "level"

linfct

Matrix. Linear functions of bhat for each combination of levels.

df

Numeric value or function with arguments (x, dfargs). If a number, that is used for the degrees of freedom. If a function, it should return the degrees of freedom for sum(x*bhat), with any additional parameters in dfargs.

dffun

Overrides df if specified. This is a convenience to match the slot names of the returned object.

dfargs

List containing arguments for df. This is ignored if df is numeric.

post.beta

Matrix whose columns comprise a sample from the posterior distribution of the regression coefficients (so that typically, the column averages will be bhat). A 1 x 1 matrix of NA indicates that such a sample is unavailable.

...

Arguments passed to update.emmGrid

Details

The arguments must be conformable. This includes that the length of bhat, the number of columns of linfct, and the number of columns of post.beta must all be equal. And that the product of lengths in levels must be equal to the number of rows of linfct. The grid slot of the returned object is generated by expand.grid using levels as its arguments. So the rows of linfct should be in corresponding order.

Value

An emmGrid object

Examples

# Given summary statistics for 4 cells in a 2 x 2 layout, obtain 
# marginal means and comparisons thereof. Assume heteroscedasticity
# and use the Satterthwaite method
levels <- list(trt = c("A", "B"), dose = c("high", "low"))
ybar <- c(57.6, 43.2, 88.9, 69.8)
s <-    c(12.1, 19.5, 22.8, 43.2)
n <-    c(44,   11,   37,   24)
se2 = s^2 / n
Satt.df <- function(x, dfargs)
    sum(x * dfargs$v)^2 / sum((x * dfargs$v)^2 / (dfargs$n - 1))
    
expt.rg <- emmobj(bhat = ybar, V = diag(se2),
    levels = levels, linfct = diag(c(1, 1, 1, 1)),
    df = Satt.df, dfargs = list(v = se2, n = n), estName = "mean")
plot(expt.rg)

( trt.emm <- emmeans(expt.rg, "trt") )
( dose.emm <- emmeans(expt.rg, "dose") )

rbind(pairs(trt.emm), pairs(dose.emm), adjust = "mvt")
[Package emmeans version 1.1.3 Index]