- People often misuse statistical terminology. Can you clarify what you mean by "I have the z-score of 2 groups". The z-score (or standard score) often refers to a single value, relative to a group. But it sounds like maybe you have the z-statistic, the result of doing a z-test on each group. Is that right?
- Do you have the underlying data, or only the z-statistic?
- When you say "relative comparison", what do you really want to test/know? Do you want to know if the two groups are unlikely to have been drawn from the same underlying distribution? Or that they have different means?
what test to use on z-scores
11 views (last 30 days)
Show older comments
Joanne Hall
on 25 Mar 2023
Commented: Star Strider
on 26 Mar 2023
Dear matlab,
I have z-scores of 2 groups. I want to compare them.
What test in matlab should I use for relative comparison using just the z scores?
Thanks in advance for any guidance!
Joanne
4 Comments
Star Strider
on 26 Mar 2023
@Joanne Hall — As I illustrated in my Answer, unless you can reconstitute the original data from the respective means and standard deviations, there is nothing you can do to compare the two groups. Standardizing them erases any differences the two groups may once have had. However if you have the original means and standard deviations from each group, and if they are normally distributed, those are all you need to use to compare them.
Again, if you no longer have the means and standard deviations, you have my sympaties.
Accepted Answer
Star Strider
on 25 Mar 2023
Since the zscore is simply a standardised method of expressing data, and if the mean values and standard deviation (std) values of each group are known, it is possible to map back to the original data and then do a valid comparison. However, if that information is not available and so it is not possible to cannot back-calculate to the original data, then your ability to discriminate the two gropus is likely lost, and no test will produce a valid comparison.
An example using random original and standardised data and the Wilcoxon ranksum test (assuming that the two groups are not paired) illustrates the issue —
x = randn(25,1);
y = randn(25,1)*3+5;
zx = zscore(x);
zy = zscore(y);
[p1,h1,stats1] = ranksum(x,y) % Original Data Are Significantly Different
[p2,h2,stats2] = ranksum(zx,zy) % Standardised Scores OF The Original Data Are Not Significantly Different
So while the original data in this example are significantly different (the ranksum test assumes that both groups have the same underlying distribution, although the distribution itself is irrelevant), the standardised scores of the same data are not.
It is not worth the effort to compare the standardised scores, since any differences between the two groups that might have originally existed are lost in the standardisation process.
You have my sympathies.
.
4 Comments
More Answers (0)
See Also
Categories
Find more on Hypothesis Tests in Help Center and File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!