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RE: st: Identify Categorical/Dichotomous and Continuous Variables


From   "Nick Cox" <n.j.cox@durham.ac.uk>
To   <statalist@hsphsun2.harvard.edu>
Subject   RE: st: Identify Categorical/Dichotomous and Continuous Variables
Date   Sun, 5 Oct 2008 17:33:21 +0100

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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