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From |
Steven Samuels <sjhsamuels@earthlink.net> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Identify Categorical/Dichotomous and Continuous Variables |

Date |
Sun, 5 Oct 2008 13:26:50 -0400 |

Agreed. -Steve On Oct 5, 2008, at 1:11 PM, Nick Cox wrote:

Good advice, but to repeat for Frank and any others puzzled: Stata does

not think of such variables as nominal, indicator, etc. If something is

(say) coded 0, 1 or missing then any user is perfectly entitled to think

of it as an indicator/dummy, etc., but Stata does not think that way.

It's in your mind, not Stata's.

Nick

n.j.cox@durham.ac.uk

Steven Samuels

To turn any variable in Stata into a nominal variable, you create

indicator variables. This is what SPSS does when you use a

categorical variable as a predictor in regression. There are two ways

of doing this in Stata: a) -xi- or b) -tab- with the -gen()- option.

See http://www.ats.ucla.edu/stat/Stata/webbooks/reg/chapter3/

statareg3.htm Section 3.3 for some examples.

On Oct 5, 2008, at 12:33 PM, Nick Cox wrote:

This is not quite true. In particular, -anova- has an idea of the

distinction. If you specify that a variable is categorical or

continuous, or imply that by default, -anova- takes action

accordingly.

But in general, as others have emphasised or implied, Stata puts the

onus on users to decide how they want variables to be treated. If you

want -foreign- in the auto data to be a binary response for -logit-,

that's fine. If you want to average it with -summarize-, that's fine

too. Sometimes, Stata will refuse to do something on principle; more

usually, it assumes that you are smart enough to know what you want to

do.

# of distinct values is, as Svend will agree, a criterion to be used

circumspectly. I often deal with rainfall data usually measured by

convention to a resolution of 0.1 mm. I bet that the number of

distinct

values met in practice is fewer than that in the typical

classifications

of death, disease or economic activity.

Nick

n.j.cox@durham.ac.uk

Svend Juul

As Martin responded: Stata has no formal distinction between

continuous and categorical numeric variables. However, the

command

codebook, compact

may tell you what you want. The -Unique- column tells you

how many "unique" (meaning different) values each variable

has.

Frank

I am new to Stata: moved from SPSS a week ago. I am hoping

that someone can help me with what I imagine is a simple

issue. I saved an SPSS file as a Stata one. I am working

my way through the user guide and the data management

manual, but I am having difficulty with confirming whether

Stata recognizes variables as continuous (or scale) or

categorical/dichotomous (or nominal). In SPSS, you can

easily identify whether the type of measure is a scale,

nominal, or string with its drop down menu in the variable

view. It would be a great help, and I would appreciate it

very much if someone would tell me the method to confirm

the data type for categorical/dichotomous and for

continuous variables? Thank you.

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**References**:**Re: st: Identify Categorical/Dichotomous and Continuous Variables***From:*Svend Juul <SJ@SOCI.AU.DK>

**RE: st: Identify Categorical/Dichotomous and Continuous Variables***From:*"Nick Cox" <n.j.cox@durham.ac.uk>

**Re: st: Identify Categorical/Dichotomous and Continuous Variables***From:*Steven Samuels <sjhsamuels@earthlink.net>

**RE: st: Identify Categorical/Dichotomous and Continuous Variables***From:*"Nick Cox" <n.j.cox@durham.ac.uk>

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