I've created tag mixed-data. I mean a mixture of variables of different types or scales.
We long have tags [continuous-data]
, [categorical-data]
, [binary-data]
, [count-data]
, [ordinal-data]
. All of them are necessary and should exist, to me. (We also have tag [nominal]
and I wonder shouldn't it be kept, dismissed or merged to [categorical-data]
.)
I think that we do need tag [mixed-data]
. In many analyses, mostly multivariate exploratory methods (cluster, factor, irt,...), but also in other as well, mixing variables of different types in one set represent a special problem to solve.
I want therefore to ask you some questions:
- Do we need that tag?
- Shall it be worded
[mixed-data]
or[mixed-type-data]
? - Shall we narrow the definition - in the excerpt - so that we don't include the (very usual) case of using mixed type predictors (continuous+categorical) in regression-like modeling in the concept of "mixed data", or include that case in the concept too - along with using mixed data in clustering, PCA, etc.?
- Other thoughts from you, please welcome.
We also have tag [nominal] and I wonder shouldn't it be kept, dismissed or merged to [categorical-data]
: Yes, I think [nominal] should be made a synonym of [categorical-data]! That was @gung's suggestion some time ago and we discussed it in a separate Meta post but you were strongly against this mapping so it was never implemented. Did you have second thoughts since then? I don't know about gung but I still think it would be a sensible tag synonym mapping. $\endgroup$mixed-data
tomixed-type-data
(as I mentioned it) soon. Then I'll select and tag questions. I'll do it, please wait a bit. $\endgroup$[mixed-data]
refer to variables with different measures, or to mixed continuous-discrete distributions, or to? $\endgroup$mixed-type-data
(that will be the tag) will refer only to mixture of variates (data columns) of different measures. $\endgroup$