This has not the least to do with Likert or Likert *scale* (which is a measurement instrument composed

of several Likert-type items), or a single Likert type item, or a Likert item response scale. If you

use the term "Likert scale", then you refer to an interval scaled measurement.

But regardless of the labeling, you have an ordinal scaled variable which was measured twice within the

same sample. If you want to know whether there was an effect of time, then this effect is included in the

difference between the ordinal scaled measurements at t1 and t2. The test for this difference is the *sign test*.

Hello,

I am afraid that the studies published in scientific litterature would disagree with your opinion and that this scale definitely has to do with a "Likert scale".

It is even called the "7-Point Likert Scale of Lower Limb Muscle Soreness" and was published in Clinical Journal of Sport Medicine (full reference : Impellizzeri FM, Maffiuletti NA. Convergent Evidence for Construct Validity of a 7-Point Likert Scale of Lower Limb Muscle Soreness: Clinical Journal of Sport Medicine 2007; 17(6): 494–496.)

I must confess that I do not know what you mean. A paired samples test does not do what you describe,

and both measures are not strictly qualitative, but ordered categorical (rank variables).

With kind regards

Karabiner

If this is true, then I would welcome some additional explanation.

If I go back to the basics of how I was taught statistic, then the very first thing to define - in order to choose a test - is :

1) to define the independant (X)/dependant (Y) variable

2) to define if these variables are qualitative/quantitative

- If X and Y are both quantitative, then a Spearman/Pearson correlation is used

- If X is quantitative and Y qualitative (or vice-versa) then there are several options (depending on the normal/non-normal distribution; the fact that the groups are paired/not-paired; the fact that the variances are equal/not equal, the fact that there are 2 groups or more than 2 groups, ...)

- If X and Y are both qualitative, then depending on the case it would either be a Fisher test, Mc nemar test, Chi2 test or Kappa test.

Do you agree with this ?

A paired sample test, such as the "student t test" or the "Wilcoxon test" is a test allowing to compare two set of data when the

**independant** variable is qualitative and the

**dependent** variable is quantitative. Let's take the following example to explain my point :

*If I have a group of 60 people, that I then : *

- measure their heart rat

- split the groupe in two (A and B). A being the test group and B being the placebo group

- give the pill to group A and nothing to group B

- measure again the heart rate of all 60 people the next day
*I can perform a statistical test to evidence "the effect that this pill has had on the heart rate" and therefore see :*

- if "there is a statistical difference before/after taking the pill for group A" (and see if there is a stastistical difference between day1 and day 2 for group B) as well as

- if "there is a statistical difference between group A and group B on the next day".
*In this case, either the people will/will not take the pill (the ***independant** variable is qualitative) and the measured variable (**dependant** variable) is the heart rate (quantitative).
*I will therefore here have measured the effect that the ***independant** variable has **on the dependant variable** (i.e., I will have measured the effect that the pill has on the heart rate), which means that :

- if I make an intragroup comparison I will have to use a "paired t test" (or wilcoxon, for non-normal distribution); and

- if I make an intergroup comparison, I will have to use a "welch test" or "t student equal variance" test (or "mann-whitney test" for non-normal distribution
*The reason these tests are chosen is very much linked to the type of variable (quantitative or qualitative). *

If, for example, I wished to see the link between two quantitative variable (e.g., the link between the weight of a mouse and the length of its tail), then I would need to perform a Pearson (or Spearman) correlation.

And if I wished to see the link between two qualitative variable (e.g., the link between taking/not taking a pill and being sick/healthy), then I would most likely need to use a Chi2 test.
There is nonetheless a HUGE difference between the example mentioned above and my original example.

In the original example, the 7-point scale (called "likert scale" by those who developed it) is a qualitative scale (not quantitative).

It therefore means here that the measured variable is qualitative, not quantitative.

I hope this explains better my viewpoint