I would think that to look at just the overall distribution of these three
time-series (I'm assuming your 3 methods of measurement yield 3 different
time-series right?) tells you very little about their respective behavior in
time; also, the distribution you estimate (histogram) is only a sample, and
for nonstationary time-series one would expect that the distribution isn't
very representative of the population (i.e., the underlying process is
continually changing somehow). So summary statistics might be a first-step,
but I would follow up with an ARIMA approach to modeling these three series.
Examine their power-spectra as well. Follow that up with something like a
PCA to see if they are somehow related in terms of variance components.

----- Original Message ----- 
From: "Euh" <[EMAIL PROTECTED]>
To: <[EMAIL PROTECTED]>
Sent: Thursday, March 04, 2004 10:28 AM
Subject: [edstat] How to compare trends ?


> 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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