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Re: st: Identify Categorical/Dichotomous and Continuous Variables
From |
Steven Samuels <[email protected]> |
To |
[email protected] |
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
[email protected]
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
[email protected]
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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