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"Statistically speaking, multivariate analysis refers to statistical
models that have 2 or more dependent or outcome variables, and
multivariable analysis refers to statistical models in which there are
multiple independent or response variables."
I thought multivariable analysis involved multiple *explanatory* (NOT
response) variables. Perhaps I'm not as fluent in the multiple
synonyms for "left-hand side" and "right-hand side" variables as I
thought? However, if it is a mistake by the authors, it is
particularly humorous given the theme of the article.
That aside, what I can't understand is why no similar emphasis has
been made regarding the correct usage of "univariate." Following the
multivariable vs. multivariate logic, why wouldn't all single outcome
analyses, including multivariable analyses, be considered univariate
analyses?
Nicole
[1] Hidalgo B, Goodman M. Multivariate or multivariable regression? Am
J Public Health. 2013 Jan;103(1):39-40. doi: 10.2105/AJPH.2012.300897.
Epub 2012 Nov 15.
On Tue, Oct 15, 2013 at 1:54 PM, Joe Canner <[email protected]> wrote:
> Nicole,
>
> I believe you are correct regarding Multivariable versus Multivariate. I remember this distinction being made by my grad school profs (Johns Hopkins School of Public Health), but it seems to be widely ignored. As Nick suggests, perhaps this distinction is mainly defended in biostatistics and epidemiology circles. See the following article for an argument from the purist side:
>
> Hidalgo B, Goodman M. Multivariate or multivariable regression? Am J Public Health. 2013 Jan;103(1):39-40. doi: 10.2105/AJPH.2012.300897. Epub 2012 Nov 15.
>
> Regards,
> Joe Canner
> Johns Hopkins University School of Medicine
>
> -----Original Message-----
> From: [email protected] [mailto:[email protected]] On Behalf Of Nicole Boyle
> Sent: Tuesday, October 15, 2013 3:51 PM
> To: [email protected]
> Subject: st: "Proper" usage: Univariate, bivariate, multivariate, multivariable
>
> 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
>
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