This is a programming question for people who like to use the ez package in R. I am accustomed to using linear mixed effects models with lmer(). Among the useful outputs of lmer (), I get a coefficient value for each of my experimental factors, and using pvals.fnc() I can easily get 95% confidence intervals (CI) to report together with the model coefficients.
I have recently started using ezANOVA, and I would like to know: Is there a mainstream way to get the same output? That is, I'd like to get a value for the coefficient of an experimental factor and a CI to go along with it. Here is sample code to make this concrete:
library(languageR) #necessary to use pvals.fnc()
library(lme4) #necessary for lmer()
library(ez) #necessary for ezANOVA
data(ANT) #load sample data
If I were using lmer, I would estimate my model and then get 95% CIs for the coefficients:
model_lmer = lmer( formula = rt ~ cue*flank + (1|subnum), data = ANT)
pvals.fnc(model_lmer, withMCMC=T)$fixed
So, for example, I know that the estimate of the interaction between cue and flank (when cue has the level "center" and flank has the level "congruent") is -3.9511 and the 95% CI is [-12.997, 5.535]
Now say that I want to run an anova by-subjects and by-items using ezANOVA, and I want to get 95% CIs for the by-subject estimates. This is my model:
model.f1 = ezANOVA(data=ANT, dv=rt,wid=subnum,within=.(cue,flank),return_aov=T)
But in the output, I don't see the model estimates when I do:
model.f1$ANOVA
And I don't know how to calculate the 95% CIs corresponding to those estimates. I think I should be able to use ezBoot() but I tried and I'm not sure how to implement it.
Any suggestions? Thanks for your help!