我尝试使用TukeyHSD(my_anova$aov)
,但却出错:
Error in UseMethod("TukeyHSD") :
no applicable method for 'TukeyHSD' applied to an object of class "c('aovlist', 'listof')"
谷歌表示没有办法用'aovlist'进行邮寄。但也许你对ezANOVA输出的post hoc有任何想法。
示例:
require(ez)
data(ANT)
rt_anova = ezANOVA(data = ANT[ANT$error==0,], dv = rt, wid = subnum, within = cue,return_aov = TRUE)
尝试使用multcomp:
require(multcomp)
glht(my_anova$aov, linfct = mcp(cue = "Tukey"))
Error in model.matrix.aovlist(model) :
‘glht’ does not support objects of class ‘aovlist’
Error in factor_contrasts(model) :
no ‘model.matrix’ method for ‘model’ found!
尝试使用lme
:
require(nlme)
lme_velocity = lme(rt ~ cue, data=ANT[ANT$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
答案 0 :(得分:2)
这不是它的ezANOVA输出,而是重复测量ANOVA。类'aovlist'通常用于此。 TukeyHSD适用于独立设计。请参阅this question及相关链接。
答案 1 :(得分:1)
您没有提供任何可重现的代码,但我猜您需要使用包multcomp:
require(multcomp)
glht(my_anova$aov, linfct = mcp(cue= "Tukey"))
(不适用于重复措施aov
,请参阅@ John的答案原因)
===更新===
您的代码适用于我(R 2.15.2,nlme 3.1-105,multcomp 1.2-15):
> data(ANT)
> lme_velocity = lme(rt ~ cue, data=ANT[ANT$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