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Science Forum Index » Statistics - Education Forum » RM ANOVA and other methods
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| greg |
Posted: Wed Mar 12, 2008 10:30 pm |
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I have a study design question I was having trouble with.
I have 2 groups (placebo & case) and 3 timepoints.
I could use 1 2-way Repeated Measures ANOVA to analyse the data, but
the timepoints would (surely) simply be treated as 3 groups, rather
than 3 ordinal points.
Is there a method that will do this for me?
(And if there isn't, how would I interpret a result that went up and
then back down again when I'm expecting a dose response?) |
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| Bruce Weaver |
Posted: Thu Mar 13, 2008 3:37 am |
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On Mar 13, 4:30 am, greg <jsg...@lycos.co.uk> wrote:
Quote: I have a study design question I was having trouble with.
I have 2 groups (placebo & case) and 3 timepoints.
I could use 1 2-way Repeated Measures ANOVA to analyse the data, but
the timepoints would (surely) simply be treated as 3 groups, rather
than 3 ordinal points.
Is there a method that will do this for me?
(And if there isn't, how would I interpret a result that went up and
then back down again when I'm expecting a dose response?)
Look up (polynomial) trend analysis. The basic concepts are discussed
here in the context of one-way (between-Ss) ANOVA, but it can also be
used for repeated measures factors:
http://davidmlane.com/hyperstat/intro_ANOVA.html
It sounds like you are expecting a significant quadratic trend.
--
Bruce Weaver
bweaver@lakeheadu.ca
www.angelfire.com/wv/bwhomedir
"When all else fails, RTFM." |
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| greg |
Posted: Thu Mar 13, 2008 10:30 pm |
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Thanks Bruce,
To be honest, I'm hoping for a linear trend in this study. A quadratic
one wouldn't make much sense in this case, and with only 3 time points
wouldn't be very convincing either. But I do have another study (not
repeated measures, 5 ordinal groups and one continuous variable) where
it looks like there might be quadratic trend (confession here to
peeking at the data halfway through). It might be very useful for that
one, thanks! |
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| Bruce Weaver |
Posted: Fri Mar 14, 2008 3:28 am |
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On Mar 14, 4:30 am, greg <jsg...@lycos.co.uk> wrote:
Quote: Thanks Bruce,
To be honest, I'm hoping for a linear trend in this study. A quadratic
one wouldn't make much sense in this case, and with only 3 time points
wouldn't be very convincing either. But I do have another study (not
repeated measures, 5 ordinal groups and one continuous variable) where
it looks like there might be quadratic trend (confession here to
peeking at the data halfway through). It might be very useful for that
one, thanks!
I just re-read your first post. I guess "expecting" was the wrong
word. It sounds like you *observed* a quadratic trend (result went
up, then back down).
--
Bruce Weaver
bweaver@lakeheadu.ca
www.angelfire.com/wv/bwhomedir
"When all else fails, RTFM." |
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| greg |
Posted: Mon Mar 24, 2008 2:31 am |
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Guest
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On Mar 14, 1:28 pm, Bruce Weaver <bwea...@lakeheadu.ca> wrote:
Quote: On Mar 14, 4:30 am, greg <jsg...@lycos.co.uk> wrote:
Thanks Bruce,
To be honest, I'm hoping for a linear trend in this study. A quadratic
one wouldn't make much sense in this case, and with only 3 time points
wouldn't be very convincing either. But I do have another study (not
repeated measures, 5 ordinal groups and one continuous variable) where
it looks like there might be quadratic trend (confession here to
peeking at the data halfway through). It might be very useful for that
one, thanks!
I just re-read your first post. I guess "expecting" was the wrong
word. It sounds like you *observed* a quadratic trend (result went
up, then back down).
--
Bruce Weaver
bwea...@lakeheadu.cawww.angelfire.com/wv/bwhomedir
"When all else fails, RTFM."
It looks like there may be a slight, weakly 'significant' unexpected
up-down pattern in one variable. In an ideal world, I'd like a method
that would take into account the fact that the groups are ordinal (in
terms of time sequence) and I'm sure there are better methods out
there.
I'd be happy to say that there was a quadratic relationship if I was
convinced there really was one, but I was concerned that by treating
the time points as different groups, the ANOVA may be giving me a
false positive. |
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| Bruce Weaver |
Posted: Mon Mar 24, 2008 9:55 am |
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greg wrote:
Quote: On Mar 14, 1:28 pm, Bruce Weaver <bwea...@lakeheadu.ca> wrote:
On Mar 14, 4:30 am, greg <jsg...@lycos.co.uk> wrote:
Thanks Bruce,
To be honest, I'm hoping for a linear trend in this study. A quadratic
one wouldn't make much sense in this case, and with only 3 time points
wouldn't be very convincing either. But I do have another study (not
repeated measures, 5 ordinal groups and one continuous variable) where
it looks like there might be quadratic trend (confession here to
peeking at the data halfway through). It might be very useful for that
one, thanks!
I just re-read your first post. I guess "expecting" was the wrong
word. It sounds like you *observed* a quadratic trend (result went
up, then back down).
--
Bruce Weaver
bwea...@lakeheadu.cawww.angelfire.com/wv/bwhomedir
"When all else fails, RTFM."
It looks like there may be a slight, weakly 'significant' unexpected
up-down pattern in one variable. In an ideal world, I'd like a method
that would take into account the fact that the groups are ordinal (in
terms of time sequence) and I'm sure there are better methods out
there.
Trend analysis *does* take the ordinal nature of the data into account.
(The standard form of trend analysis treats the explanatory variable
as interval scaled with a constant step size between adjacent
categories.) It is not at all appropriate in the case of a purely
nominal explanatory variable.
Quote: I'd be happy to say that there was a quadratic relationship if I was
convinced there really was one, but I was concerned that by treating
the time points as different groups, the ANOVA may be giving me a
false positive.
--
Bruce Weaver
bweaver@lakeheadu.ca
www.angelfire.com/wv/bwhomedir
"When all else fails, RTFM." |
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| greg |
Posted: Tue Mar 25, 2008 5:35 am |
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Thanks Bruce,
I've tried it out in SPSS with some artificial data to get a hang of
the method and all the results for trends (using the contrast feature)
seem to make sense. Now I can look at both Linear & Quadratic trends &
have a bit more confidence in my results.
Hurrah! |
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