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st: RE: RE: rmanova or anova with repeated command, what to use?
From
"Pieter-Jan" <[email protected]>
To
<[email protected]>
Subject
st: RE: RE: rmanova or anova with repeated command, what to use?
Date
Wed, 5 Oct 2011 21:04:14 +0200
Dear George,
First of all thanks for the rmanova ado.
We used the day 1 test to see if the lung function parameters were subjected
to a diurnal variation we had to correct for in the other two experimental
days. Both day 2 and day 3 trials were performed under hyperbaric conditions
in which we want to study the effect of hyperbaric oxygen on these lung
function parameters. Exposure to air was used to see if any pressure effects
was of influence on the lung function.
I will try your suggestion to organize the results in another way to look
for any treatment effects.
Again, many thanks for your reply and your suggestion and of course for the
rmanova ado.
Sincerely Yours,
Pieter-Jan van Ooij
-----Oorspronkelijk bericht-----
Van: [email protected]
[mailto:[email protected]] Namens Hoffman, George
Verzonden: 5 oktober 2011 12:35
Aan: [email protected]
Onderwerp: st: RE: rmanova or anova with repeated command, what to use?
You might think about, and then organize, the dataset a little differently.
You want to compare the effects of two treatments on lung function, measured
repeatedly over time, before and after initiation of treatment.
You have two treatment groups (air, O2) and two (or three) 'conditions'
(baseline, active day 2, active day 3).
(question: is day 2 hyperbaric, and day 3 normobaric? Or are both under the
same conditions, in which case you experiment would have only two
conditions)
In either case, you need to split your 'group' variable into two variables
that identify the treatment group (air, O2) and condition (baseline,
active).
ID group condition hour
1,2...13 1,2 1,2 (3) 0,2,....22
This would allow you to use anova y group##cond, rep(hour) to look at
treatment effects.
Alternatively, you could code time as sequential hours form 0-72, then
xtdes, i(id) t(hour) and use the xt functions.
I hope this helps a little.
rmanova and anova should give similar results set up this way.
George Hoffman
-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Pieter-Jan
Sent: Tuesday, October 04, 2011 2:58 PM
To: [email protected]
Subject: st: rmanova or anova with repeated command, what to use?
Dear statalisters,
Some time ago we performed a randomized crossover study in which we
monitored the lung function of a group of volunteers during three days. Day
1 was used to determine baseline lung function whereas day 2 and 3 were used
to monitor lung function after inhaling either placebo (air) or active gas
(oxygen) under hyperbaric condition. During each measurement day lung
function was measured 6 times. All variables and observations were put in a
dataset which initially had the following format:
ID Group Time Result1 etc
1 0 0 6.19
2 0 0 5.97
. . . .
. . . .
13 2 22 5.33
Etc
ID exist of 13 persons (nr 1-13)
Group: 0 (baseline), 1 (placebo), 2 (active)
Time: pre, 0, 2, 4, 8, 12, 22 hours after exposure
We want to perform a repeated measures anova as all subject performed all
three test days which makes the groups not independent. The format we had in
mind was to search for differences between the groups at a specific time
point and to look for a correlation between Result1, etc and variable time.
I found two possibilities of doing a repeated measures anova using Stata
9.2:
1. Using Ado rmanova written by George Hoffman
2. Using anova with command repeated.
I tried both commands but they gave some contradictory results. To gave an
example I put in the log results of one test:
. rmanova FEF50 id time group
ANOVA for var FEF50 by subject ID
n=198 df=32 R2=.90011879
between effect: group
Source | Partial SS df MS F Prob >
F
-------------+----------------------------------------------------
group | 94.488177 2 47.2440885 0.17
0.8420
id*group | 8196.56138 30 273.218713
within effect: time
Source | Partial SS df MS F Prob >
F
-----------+----------------------------------------------------
Time | 218.17681 17 12.83393 1.78
0.0343
Residual | 1226.78373 170 7.21637487
. anova FEF50 id group time, repeated(group time)
Number of obs = 198 R-squared =
0.8668
Root MSE = 2.68633 Adj R-squared =
0.8457
Source | Partial SS df MS F Prob >
F
-----------+----------------------------------------------------
Model | 7984.27781 27 295.713993 40.98
0.0000
|
Id | 7766.101 10 776.6101 107.62
0.0000
group | 45.8076387 2 22.9038193 3.17
0.0443
time | 123.688633 15 8.24590887 1.14
0.3222
|
Residual | 1226.78373 170 7.21637487
-----------+----------------------------------------------------
Total | 9211.06154 197 46.7566576
Between-subjects error term: id
Levels: 11 (10 df)
Lowest b.s.e. variable: id
Repeated variable: group
Huynh-Feldt epsilon =
0.6682
Greenhouse-Geisser epsilon =
0.6227
Box's conservative epsilon =
0.5000
------------ Prob > F
------------
Source | df F Regular H-F G-G Box
-----------+----------------------------------------------------
group | 2 3.17 0.0443 0.0651 0.0685
0.0784
Residual | 170
-----------+----------------------------------------------------
Repeated variable: time
Huynh-Feldt epsilon =
0.4478
Greenhouse-Geisser epsilon =
0.2469
Box's conservative epsilon =
0.0667
------------ Prob > F
------------
Source | df F Regular H-F G-G Box
-----------+----------------------------------------------------
Time | 15 1.14 0.3222 0.3460 0.3482
0.3073
Residual | 170
-----------+----------------------------------------------------
. log close
In rmanova there is a significant correlation with FEF50 and time
(p=0.0343), while in the anova with repeated command test there is none such
correlation. Can anyone advise us which option we should use: rmanova or
anova with the repeated command? Many thanks.
Sincerely Yours,
Pieter-Jan van Ooij
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