if X and Y are correlated, any monotone function may yield a significant p-value. You need information not present in the data set.
Euh <[EMAIL PROTECTED]> wrote:
Euh <[EMAIL PROTECTED]> wrote:
Hi all,
I'm following the time course of a certain variable by using three
independent measurement techniques (for which I can estimate the
variance associated with the measurment)
I can't really assume any function to describ the evolution of the
variable over time (linear, quadratic, etc). Is there a way to compare
the results and assess if all the methods give similar results ?
ANOVA analysis at each time ?
An example would be:
Method 1 Method 2 Method 3
mean stdev mean stdev mean stdev
t1 24.6 6.4 31.0 13.8 15.5 5.7
t2 123.5 87.6 155.2 71.5 62.3 20.0
t3 174.0 33.8 142.7 46.4 75.8 18.9
t4 210.6 91.2 113.6 26.8 101.9 45.1
t5 396.4 25.4 263.9 16.5 209.3 11.7
t6 303.7 66.7 271.9 156.6 216.9 172.1
t7 153.6 93.4 261.0 225.6 76.0 41.7
t8 250.9 140.7 289.5 122.7 93.7 28.1
.
.
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