<p>This is non-parametric statistics, the mean requires conformation to the normal distribution (but there are exceptions), or perhaps better put it requires a fixed relationship between mean and standard deviation. Non-parametric stats always use the median and are distribution free. Wilcoxon test/ Mann-Whitney U test  are used to replace t-test. The Kruskal-Wallis test replaces the 1-way ANOVA
Finally the Friedman test replaces 2-way ANOVA but has its critiques.  The t- and ANOVA tests require normality, F-max is one approach to determine normality.</p>

CC BY-SA 4.0
2020-01-01T00:51:14.067Z
Thanks. upvoted for the response
The Great
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2020-03-13T12:34:02.970Z
:-) thanks @subhash, likewise.
M__
CC BY-SA 4.0
2019-12-31T14:48:21.540Z
2024-02-09T15:31:29.483Z
2024-02-09T15:31:29.483Z
M__
<p>Another viewpoint could be : statistically significant implies use of sampling theory to establish presence of significant difference  between  case and control groups. The "clinical " significance seems to test for correctness or validity of measures of variables. Apparenty, the measurement theory is meant for checking validity of data - the difference  could arise on account of incorrect measurements. The non-parameteric tests -  it seems - take care of measurement errors and hence, produce perhaps more reliable results.</p>

CC BY-SA 4.0
2020-03-13T03:15:46.337Z
Thanks upvoted for the response
The Great
CC BY-SA 4.0
2020-03-12T12:52:22.393Z
2020-03-12T12:52:22.393Z
Subhash C. Davar
<p>I am working on a clinical data analysis project and am from IT domain.</p>

<p>While I am analyzing the data, I came to know that though some of the variables are not statistically significant, they are clinically significant.</p>

<p>I also read that difference in median values between case and control group for variables is used as a measure to indicate clinical significance</p>

<p>Can someone help me understand this with a simple example as to why difference in median between groups is considered for clinical significance?</p>

CC BY-SA 4.0
2023-06-10T08:08:32.387Z
nice and a great question
Subhash C. Davar
<database><errors><validation><p-values>
Difference between clinical significance and statistical significance
# Difference between clinical significance and statistical significance

(Asked by: username_0 on 2019-12-29)

I am working on a clinical data analysis project and am from IT domain.

While I am analyzing the data, I came to know that though some of the variables are not statistically significant, they are clinically significant.

I also read that difference in median values between case and control group for variables is used as a measure to indicate clinical significance

Can someone help me understand this with a simple example as to why difference in median between groups is considered for clinical significance?

**Tags:** database, errors, validation, p-values
> **Comments:**
> **username_1**: nice and a great question  

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## 2 answers

### Answer by username_1 on 2020-03-12. Score: 2 | Accepted answer

Another viewpoint could be : statistically significant implies use of sampling theory to establish presence of significant difference between case and control groups. The "clinical " significance seems to test for correctness or validity of measures of variables. Apparenty, the measurement theory is meant for checking validity of data - the difference could arise on account of incorrect measurements. The non-parameteric tests - it seems - take care of measurement errors and hence, produce perhaps more reliable results.

> **Comments:**
> **username_0**: Thanks upvoted for the response  

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### Answer by username_2 on 2019-12-31. Score: 3

This is non-parametric statistics, the mean requires conformation to the normal distribution (but there are exceptions), or perhaps better put it requires a fixed relationship between mean and standard deviation. Non-parametric stats always use the median and are distribution free. Wilcoxon test/ Mann-Whitney U test are used to replace t-test. The Kruskal-Wallis test replaces the 1-way ANOVA
Finally the Friedman test replaces 2-way ANOVA but has its critiques. The t- and ANOVA tests require normality, F-max is one approach to determine normality.

> **Comments:**
> **username_0**: Thanks. upvoted for the response  
> **username_2**: :-) thanks @subhash, likewise.  

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