Ricardo Ovaldia <[email protected]> asks:
> I was approached by an investigator with the following
> problem. He had two groups of experimental rats, 10
> diabetic and 10 non-diabetic. Each of these rats had
> one liter of 10 pups (average). On each of the pups a
> series of biochemicals were measured. He wants me to
> compare the mean value of these biochemicals from the
> pumps from diabetic moms to the pups from non-diabetic
> pups. He then suggested that I do a simple t-test
> comparing the means of the two pup groups. I pointed
> out that the observations are not independent because
> of several pups from the same liter and that the liter
> effect needs to be taken into account.
>
> How can I set this up in Stata?
Assuming I understand your setup, you have a nested ANOVA model.
I ran the following commands to create some fake data that I think
has a similar form as yours.
clear
set obs 2
gen group = _n
expand 10
sort group
qui gen mom = _n in 1/10
qui replace mom = mom[_n-10] in 11/20
set seed 32981
gen z = 10 + round(uniform()*4-2,1)
expand z
drop z
bysort group mom : gen pup = _n
gen y = uniform()*8 + group
compress
I then looked at a table of pup counts and y value means for each
group (meaning diabetic & nondiabetic moms) and each mom within
group. The nested ANOVA results are then shown.
. table mom group, c(mean y freq)
------------------------------
| group
mom | 1 2
----------+-------------------
1 | 4.290885 5.353604
| 11 8
|
2 | 5.389515 6.748766
| 9 9
|
3 | 4.533185 6.990387
| 9 12
|
4 | 4.732775 5.633358
| 8 10
|
5 | 6.142506 4.981017
| 10 8
|
6 | 5.124625 5.217069
| 9 10
|
7 | 5.285787 5.418501
| 11 11
|
8 | 5.234306 6.799588
| 11 9
|
9 | 5.171794 6.379981
| 8 9
|
10 | 6.112025 6.664215
| 10 8
------------------------------
. anova y group / mom|group /
Number of obs = 190 R-squared = 0.1047
Root MSE = 2.40589 Adj R-squared = 0.0046
Source | Partial SS df MS F Prob > F
-----------+----------------------------------------------------
Model | 115.021745 19 6.05377604 1.05 0.4119
|
group | 31.203949 1 31.203949 6.80 0.0178
mom|group | 82.6298147 18 4.59054526
-----------+----------------------------------------------------
mom|group | 82.6298147 18 4.59054526 0.79 0.7065
|
Residual | 984.009577 170 5.78829163
-----------+----------------------------------------------------
Total | 1099.03132 189 5.81498054
I added a little group effect into my fake data (notice the
p-value of .0178).
Ken Higbee [email protected]
StataCorp 1-800-STATAPC
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