Doesn't that imply a relationship between the observations though? Wouldn't
it be equally valid to end up with them lined up like
+-------------------------+
| batch assay1 assay2 |
|-------------------------|
1. | Btch1 5400 .905 |
2. | Btch1 5320 .898 |
3. | Btch1 5670 .9 |
4. | Btch2 8600 .943 |
5. | Btch2 7840 .955 |
6. | Btch2 7550 .962 |
In the original line-up, the coefficient of determination is 0.968. In the
second one above, its 0.8.
-----Original Message-----
From: Scott Merryman [mailto:[email protected]]
Sent: Monday, May 10, 2004 6:42 PM
To: [email protected]
Subject: st: RE: unpaired regression
How about lining up the measurements?
Something like
. l
+-------------------------+
| batch assay1 assay2 |
|-------------------------|
1. | Btch1 5400 . |
2. | Btch1 5320 . |
3. | Btch1 5670 . |
4. | Btch1 . .9 |
5. | Btch1 . .905 |
|-------------------------|
6. | Btch1 . .898 |
7. | Btch2 8600 . |
8. | Btch2 7840 . |
9. | Btch2 7550 . |
10. | Btch2 . .962 |
|-------------------------|
11. | Btch2 . .955 |
12. | Btch2 . .943 |
+-------------------------+
. by batch: replace assay2 = assay2[_n +3]
(12 real changes made, 6 to missing)
. drop if assay1 == .
(6 observations deleted)
. l
+-------------------------+
| batch assay1 assay2 |
|-------------------------|
1. | Btch1 5400 .9 |
2. | Btch1 5320 .905 |
3. | Btch1 5670 .898 |
4. | Btch2 8600 .962 |
5. | Btch2 7840 .955 |
|-------------------------|
6. | Btch2 7550 .943 |
+-------------------------+
Scott
________________________________________
From: [email protected]
[mailto:[email protected]] On Behalf Of Wallace, John
Sent: Monday, May 10, 2004 7:48 PM
To: '[email protected]'
Subject: st: unpaired regression
I have two measures of batch performance on which I'd like to perform a
regression.� The measurements are taken on separate samples from the batch,
and typically look something like:
����������� Assay1 Assay2
Btch1��� 5400���� ����
Btch1��� 5320���� ����
Btch1��� 5670���� ����
Btch1��������������� 0.900
Btch1��������������� 0.905
Btch1��������������� 0.898
Btch2��� 8600���� ����
Btch2��� 7840���� ����
Btch2��� 7550���� ���
Btch2��������������� 0.962
Btch2��������������� 0.955
Btch2��������������� 0.943
...etc (on for multiple batches which show correlated measures for the two
assays)
-collapse- ing them to batch averages and then performing the regression is
one approach, but it doesn't take variance of the measures themselves into
account in the regression.� Is there a system for performing this type of
analysis?
�
Thanks,
John Wallace�|�Research Associate�| Test Method Development
AFFYMETRIX, INC. | 3380 Central Expressway | Santa Clara, CA 95051 | Tel:�
408-731-5574 | Fax:� 408-481-0435
�
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