s******n
发帖数: 95 | 1 I have 4 independent groups, one is the control group and the other three
are treatment groups.
and I have 31 study days, so I have a couple of data for every particular
day in every group.
so it's something like this:
day 1 day 2.....................................day
31
control group a e ......................
b f ...........
c g .........
d h . | s******n
发帖数: 95 | | l******r
发帖数: 18699 | 3 if you test it for each particular day,which means you drop the day effect,
then why use a repeated measurement model?
I guess in most of the situations, people tend to consider day effect,
otherwise, some useful information will be lost. in this case, a repeated
measurement anova is a good choice
day
【在 s******n 的大作中提到】
: I have 4 independent groups, one is the control group and the other three
: are treatment groups.
: and I have 31 study days, so I have a couple of data for every particular
: day in every group.
: so it's something like this:
: day 1 day 2.....................................day
: 31
: control group a e ......................
: b f ...........
: c g .........
| b*****n
发帖数: 685 | 4 有missing data你的ANOVA就不好用了。这个是longitudinal data的hypothesis test
问题，有点麻烦，不过parametric和nonpara的方法应该都有，查查paper了，比如
Jianqing Fan的。 | D******n
发帖数: 2836 | 5 repeated measurement and then do contrast at each specific day levels with
multiple comparison adjustment.
but as some1 pointed out, why are u so interested in each particular day
level? it is usually not the question to ask.
day
【在 s******n 的大作中提到】
: I have 4 independent groups, one is the control group and the other three
: are treatment groups.
: and I have 31 study days, so I have a couple of data for every particular
: day in every group.
: so it's something like this:
: day 1 day 2.....................................day
: 31
: control group a e ......................
: b f ...........
: c g .........
|
|
