Post hoc tests with ezANOVA output

Question

I tried to use TukeyHSD(my_anova$aov) but it gives an error:

Error in UseMethod("TukeyHSD") :
no applicable method for 'TukeyHSD' applied to an object of class "c('aovlist', 'listof')"

Google says that there is no way to post hoc with 'aovlist'. But maybe you have any idea about post hoc with ezANOVA output.

Example:

require(ez)
data(ANT)
rt_anova = ezANOVA(data = ANT[ANT$error==0,], dv = rt, wid = subnum, within = cue,return_aov = TRUE)

Try to use multcomp:

require(multcomp)
glht(my_anova$aov, linfct = mcp(cue = "Tukey"))

Error in model.matrix.aovlist(model) : 
  ‘glht’ does not support objects of class ‘aovlist’
Error in factor_contrasts(model) : 
  no ‘model.matrix’ method for ‘model’ found!

Try to use lme:

require(nlme)
lme_velocity = lme(rt ~ cue, data=ANT[ANT$error==0,], random = ~1|subnum)

Error in .Call("La_chol", as.matrix(x), PACKAGE = "base") : 
  Incorrect number of arguments (1), expecting 2 for 'La_chol'



> sessionInfo()
R version 2.15.2 (2012-10-26)
Platform: i386-w64-mingw32/i386 (32-bit)

locale:
[1] LC_COLLATE=Russian_Russia.1251  LC_CTYPE=Russian_Russia.1251    LC_MONETARY=Russian_Russia.1251 LC_NUMERIC=C                    LC_TIME=Russian_Russia.1251    

attached base packages:
[1] splines   stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] nlme_3.1-108     multcomp_1.2-15  survival_2.37-2  mvtnorm_0.9-9994 ez_4.1-1         stringr_0.6.2    scales_0.2.3     reshape2_1.2.2   plyr_1.8         memoise_0.1     
[11] mgcv_1.7-22      lme4_0.999999-0  Matrix_1.0-10    lattice_0.20-13  ggplot2_0.9.3    car_2.0-15       nnet_7.3-5       MASS_7.3-23     

loaded via a namespace (and not attached):
 [1] colorspace_1.2-1   dichromat_2.0-0    digest_0.6.2       grid_2.15.0        gtable_0.1.2       labeling_0.1       munsell_0.4        proto_0.3-10       RColorBrewer_1.0-5
[10] stats4_2.15.0      tools_2.15.0

Answer 1

It's not that it's ezANOVA output but that it's a repeated measures ANOVA. The class 'aovlist' is typically for that. TukeyHSD is for independent designs. See this question and related links there.

Answer 2

You don't give any reproducible code, but my guess is that you need to use the package multcomp:

require(multcomp)
glht(my_anova$aov, linfct = mcp(cue= "Tukey"))

(does not work with repeated measures aov, see @John's answer why)

===Update===

Your code works for me (R 2.15.2, nlme 3.1-105, multcomp 1.2-15):

> data(ANT)
> lme_velocity = lme(rt ~ cue, data=ANT[ANT$error==0,], random = ~1|subnum)
> glht(lme_velocity, linfct = mcp(cue= "Tukey"))

     General Linear Hypotheses

Multiple Comparisons of Means: Tukey Contrasts


Linear Hypotheses:
                      Estimate
Center - None == 0     -41.872
Double - None == 0     -47.897
Spatial - None == 0    -86.040
Double - Center == 0    -6.026
Spatial - Center == 0  -44.169
Spatial - Double == 0  -38.143