part 2.
Ordinal variables come in two flavors. In purely ordinal data the number of
distinct values is pretty much the same as the number of cases. In ordered
category variables, there are only a few values that a variable may take, but
the intervals are perceived as very different.
Interval variables have ordered values and the intervals between values are not
severely discrepant from each other.
Ratio variables have some kind of meaningful zero point.
I would usually consider months interval data if considering more than a few.
Level of aggression, or seed size, I would consider interval level if there were
four or more categories and care had been taken to make the intervals equal
appearing (e.g., anchoring with numeric stimulus labels.)
I would tend to consider Likert-scales variables as interval especially if they
were to be used in a summative scale.
Poorly written questions can often necessitate treating variables as lower
levels of measurement.
It is possible, using methods of psychophysics, to evaluate how people use a
particular response scale.
Dual Scaling can be used to evaluate how much difference it makes to assume
different levels of measurement.
Voltolini wrote:
> Hi,
>
> I have a doubt about ordinal variables !
>
> I understand that months (jan., feb., mar.) and level of aggression (low,
> medium, high) can be accepted as qualitative ordinal variables but........
> my doubt is.....
>
> What about variables like seed size when using categories like small, medium
> and large or... level of mutation as rare and frequent ? Is these variables
> qualitative ? May I use these cases as examples of qualitative and ordinal
> variables ?
>
> I am in doubt because the size of seeds or the frequency of mutations are
> measurements and counts !
>
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