Re: st: "Proper" usage: Univariate, bivariate, multivariate, multivariable

[Alfonso Sanchez-Penalver <oneiros_spain@yahoo.com>]

Hi Nick,

Yes that's true, but we could make the argument that covariance (and hence correlation) comes from the co-movement of the deviations from the mean of the two variables, which are the errors.

Alfonso Sánchez-Peñalver

> On Oct 15, 2013, at 4:36 PM, Nick Cox <njcoxstata@gmail.com> wrote:
> 
> I'd suggest that "bivariate" also applies to discrete variables and to
> variables just taken two at a time, with no question of an error term.
> Historically, for example, Pearson correlation was just a property of
> a bivariate normal distribution, with no model with error terms
> invoked.
> Nick
> njcoxstata@gmail.com
> 
> 
> On 15 October 2013 21:11, Alfonso Sanchez-Penalver
> <oneiros_spain@yahoo.com> wrote:
>> Hi Nicole,
>> 
>> To me a bivariate (and this can be extended to multivariate very straight forwardly) is one where there are two error terms that come from the same distribution, and thus they follow a bivariate distribution. Usually this is because you are trying to estimate the expected value of two dependent variables with two different equations, and the errors are not independent across equations. Anyone understands this differently?
>> 
>> Alfonso Sánchez-Peñalver
>> 
>>> On Oct 15, 2013, at 3:51 PM, Nicole Boyle <nicboyle@gmail.com> wrote:
>>> 
>>> Hello all,
>>> 
>>> There are some terms commonly used in the literature that seem (to me)
>>> technically misused. Nick Cox addressed a similar question
>>> previously*, but I'm unfortunately still confused as to the proper
>>> usage of these terms.
>>> 
>>> My understanding:
>>> 
>>> (1) Multivariable: Model with more than one exposure var and one outcome var.
>>> 
>>> (2) Multivariate: Model with one or more exposure vars and multiple
>>> outcome vars.
>>> 
>>> (3) Multivariable model != Multivariate model
>>> 
>>> (4) Univariate: Not a true model, but just looks at distribution of
>>> one "exposure" var within a group. This method may be repeated across
>>> multiple groups, e.g. demographics table with no test statistics. (In
>>> my humble opinion, this should be instead termed "univariable" to
>>> indicate a single variable, since "univariate" seems to imply a model
>>> with one outcome variable and an undefined number of exposure vars.)
>>> 
>>> (5) Bivariate: Model with one exposure var and one outcome var. (In my
>>> very novice opinion, this should instead be termed "bivariable" to
>>> indicate two variables, since "bivariate" seems to imply two outcome
>>> variables with an undefined number of exposure vars.)
>>> 
>>> (6) Univariate!=Bivariate
>>> 
>>> I've decided to run this by you all while writing what feels like a
>>> strange sentence: "Univariate and multivariable Cox proportional
>>> hazards models..." Perhaps this should be "Bivariate and
>>> multivariable" or even "Bivariable and multivariable"?
>>> 
>>> What would be considered proper usage (where "proper usage" might be
>>> defined as technically correct, or might even be defined as
>>> technically incorrect but widely accepted)?
>>> 
>>> Thanks so much for your consideration,
>>> Nicole Boyle
>>> 
>>> * http://www.stata.com/statalist/archive/2009-02/msg00398.html
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