# How to return means from Effects package? [closed]

Is there a way to return a matrix of means for levels of a factor using effect() in R? I see if you simply call an effect object you get the values printed, but I would like a matrix of these values that can be operated on. You can do this for the lower and upper confidence intervals like this:

ef1 <- effect("factor", analysis1)
ef1$lower but there doesn't seem to be a returnable matrix of means. • Which package is 'effect' in? Nov 4, 2012 at 4:05 ## 1 Answer It is always a good idea to inspect an R object with str or by directly looking at the print/summary method: in this case you can type effects:::summary.eff at R prompt and see how it works. Here is a toy example, for a linear model (for a GLM, you'll need to take care of the type of fitted values, which can be on the link or response scale): set.seed(98) n <- 60 x <- runif(n) g <- gl(2, n/2, n, labels=paste("g", 1:2, sep="")) y <- 0.3 + 1.5 * x + 0.8 * as.numeric(g) + rnorm(n) d <- data.frame(y, x, g) xyplot(y ~ x, data=d, groups=g, type=c("p","r")) summary(m <- lm(y ~ x + g, data=d)) library(effects) summary(e <- effect("g", m)) data.frame(fit=e$fit, lci=e$lower, uci=e$upper, row.names=levels(g))

The last command yields the desired quantities:

fit      lci      uci
g1 1.671264 1.266193 2.076336
g2 2.520784 2.115712 2.925855