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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