Edit: I would like to test the time effect over three times and inside group. I was looking about ANOVA repeated measures but it looks very confusing (time effect, interaction effect... I'm sometimes lost about what i'm testing). In non-parametric conditions i have no idea about what to perform. If I can run code in R and obtain significant letter between times inside groups it would be perfect. Here is you ll find my data and code i used so far. column moda is for Group, time for time and unified is a variable measured.
I have three dependent groups and for each group I have measurements overtime (t0,t14,t29). I'm looking to perform an ANOVA repeated measures to know if inside one group if there is difference. Here is my data:
structure(list(moda = structure(c(3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("BS1",
"HW1", "PG"), class = "factor"), time = c("t0", "t0", "t0", "t0",
"t0", "t0", "t0", "t0", "t0", "t0", "t0", "t0", "t0", "t0", "t0",
"t0", "t0", "t0", "t0", "t0", "t0", "t0", "t0", "t0", "t0", "t0",
"t0", "t0", "t14", "t14", "t14", "t14", "t14", "t14", "t14",
"t14", "t14", "t14", "t14", "t14", "t14", "t14", "t14", "t14",
"t14", "t14", "t14", "t14", "t14", "t14", "t14", "t14", "t14",
"t14", "t14", "t14", "t29", "t29", "t29", "t29", "t29", "t29",
"t29", "t29", "t29", "t29", "t29", "t29", "t29", "t29", "t29",
"t29", "t29", "t29", "t29", "t29", "t29", "t29", "t29", "t29",
"t29", "t29", "t29", "t29"), unified = c(1.5, 1.5, 2, 1, 1.5,
1.2, 1, 2.4, 1.3, 1.4, 1.7, 2, 1.8, 2.3, 2.5, 2.5, 1.5, 1.5,
2, 2.1, 1.8, 1.3, 2, 1.5, 2, 3.5, 1.5, 1.7, 1.2, 1.2, 1.3, 1,
4, 2, 0.5, 2, 1, 3, 6, 3, 2, 3.4, 5.3, 4, 1, 54, 3, 2.5, 2, 3.52,
3, 7, 2, 8, 3.4, 1, 1.65, 1.8, 1.9, 1.7, 1.8, 1.9, 1, 2, 1.7,
8, 5, 3.5, 5, 5.8, 2, 3.8, 1, 8, 8, 9.9, 1, 6.8, 8, 3, 9.6, 8.6,
3, 9)), row.names = c(NA, -84L), class = "data.frame")`
I tried this code
`fit <- aov(dflong1$unified ~ dflong1$time + Error(dflong1$moda/dflong1$time), data = dflong1)
library(agricolae)
TukeyHSD(fit)
bbb <- HSD.test(fit,"yyy",group=TRUE)
summary(fit)
But the post HOC tukey can't handle it. So i try another way:
lme_velocity = lme(dflong1$unified ~ dflong1$time, data=dflong1, random = ~1|dflong1$moda)
anova(lme_velocity)
require(multcomp)
summary(glht(lme_velocity, linfct=mcp(Material = "Tukey")), test = adjusted(type = "bonferroni"))
I tried to follow the question here Post hoc test after ANOVA with repeated measures using R but i got this error:
lme_velocity = lme(dflong1$unified ~ dflong1$time, data=dflong1, random = ~1|dflong1$moda, na.action = na.exclude)
Error in model.frame.default(formula = ~dflong1 + unified + time + moda, : invalid type (list) for variable 'dflong1'
How can i do so, to obtain significant letters following a postHOC after an ANOVA, like a simple ANOVA? Is it correct if I try to subset my data before by groups and then perform an Anova like this
aov(dflong1$unified~dflong1$time,paired = TRUE, alternative = "two.sided")
