Hi all,
I am also interested in determining statistical difference between the
histogram distribution of two samples (i.e. -/+ Rx), but find this K-S stuff
very confusing. My simple question is: Is it possible to just do the
experiment 3 independent times and use basic standard deviation/t-test
statistics? If so, does one use the mean fluorescent intensity or peak
fluorescent intensity from the experiments for calculating the difference?
Thanks for any/all answers and help.
Sincerely,
James Liou
At 12:38 PM 10/12/99 +0100, Ulrik Sprogøe-Jakobsen wrote:
>
> My two cents...
>
> The use of K-S or other appropriate statistics to the comparison of two
> histograms (e.g. sample A versus sample B) will reveal the true statistical
> difference (i.e. either a p-value or a confidence interval). Given the high
> number of events (typically 5 - 10,000 or more), the uncertainty of the mean
> (aka. standard error of the mean) is very very small, even though the
> distribution of each histogram is broad and overlapping. Consequently, even
> the smallest difference in mean arbitrary fluorescence of sample A versus
> sample B, is perceived as statistically significant. Therefore, as reported
> to this list, running the same sample twice, will often lead to statistical
> significance when comparing results of the two runs by the K-S test.
>
> However, this is not what we really want to know !!!
>
> What we want to know is: as evaluated by measurement of fluorescence, does
> sample A belong to population of cells (or individuals) different from that
> of sample B ?
>
> To answer this question we have to know the variation in mean (geometric mean
> or median) fluorescence when running the same sample multiple times on the
> flow cytometer. Next, to compare the difference of mean fluorescence of
> sample A and sample B with this uncertainty of the mean. If the former is
> bigger than the latter, it may be concluded that sample A and sample B belong
> to two different populations of cells. Formally, this may be expressed as:
>
> Mean fluoresc. sample A - mean fluoresc. sample B > SQRoot 2 x standard error
> of the mean (of fluorescence measurement)
>
> To conclude, the relevant comparison is not that of 2 means from 2
> distributions of events (each from a single run), but the comparison of 2
> means from 2 distributions of means (from multiple runs). In the latter case,
> knowledge of a general uncertainty of measurement of mean fluorescence (CV%
> or standard deviation), may substitute for the repeat measuring of the 2
> samples, according to the abovementioned formula.
>
> Please note: The above does not take into account the variations introduced
> by staining, lysing, washing, etc, only the crude variation in fluorescence
> measurement by the flow cytometer.
>
>
> Please comment,
>
>
> Ulrik Sprogoe-Jakobsen, M.D.
>
> Dept. Clinical Immunology
> Odense University Hospital
> 5000 Denmark
>
> E-mail: ulrik.sprogoe-jakobsen@ouh.dk
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