A measure of variability/dispersion that captures only one direction of change I am conducting a study trying to correlate changes in a biologic parameter (e.g., blood bilirubin concentration) with clinical outcomes (e.g., bleeding).
I have found that variability in such parameter over time appraised with standard deviation (SD) and coefficient of variation (CV) correlates strongly with events.
However, I am afraid that positive changes (i.e. increases) are clinically relevant, whereas decreases not. Unfortunately, I believe that SD and CV are directionally uninformative.
Is there a measure of variability/dispersion that captures direction of change, or that computes only change in one direction?
A potential solution could be to discard/censor decreases… but I am afraid this could be inappropriate.

If you are concerned with a measure of variability / dispersion that captures the direction of change, then potentially standardizing your data can be of use.
Standardizing (also sometimes called z-transform) converts your data samples into z-scores. Z-scores, unlike standard deviation, can be negative or positive. A negative z-score, say $-2$, indicates the sample is two standard deviations below the mean. Vice versa, a z-score = $2$ indicates the sample is two standard deviations above the mean.
Thus, by standardizing your data, you now have z-scores which is a measure of variability and captures the direction of that variability (in terms of negative and positive z-scores).
The formula for standardization is:
$z_i = \frac{x_i - \bar{x}}{s}$
where
$z_i$ = z-score of sample $i$
$x_i$ = original data point
$\bar{x}$ = sample mean
$\sigma$ = standard deviation of the sample
Also, here is a link with a few examples.
