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daentervar(var1 [,var2 ...] [,silent:T]), var1, var2 ... names
  or numbers of variables to be entered

Keywords: classification, discrimination, stepwise
daentervar(j), where j is a positive integer, enters dependent variable
j as part of a stepwise dependent variable selection, usually as one
stage in stepwise discriminant analysis.  This is what is sometimes
called a "forward" step.  It is an error if variable j is already an
"in" variable.

daentervar() updates variable _DASTEPSTATE which encapsulates the
current state of the variable selection process and prints a report with
the new values of F-to-enter or F-to-remove, and their P-values.  See
topic '_DASTEPSTATE' and dastepsetup() for more details.  It returns a
copy of the updated _DASTEPSTATE as an invisible variable that can be
assigned but is not normally printed.

You normally choose the variable to enter as the variable with the
largest value of F-to-enter as printed by macro dastepsetup(),
dastepstatus() or a preceding use of daentervar()

daentervar(varname), where varname is the quoted or unquoted name of
a variable in the model, does the same.  Thus if the original data
matrix had column labels "SepLen", "SepWid", "PetLen" and "PetWid",
either daentervar(SepWid) or daentervar("SepWid") would be equivalent
to daentervar(2).

daentervar(j1, j2, ...) and daentervar(varname1, varname2, ...)
successively enter several variables, printing a report after each is
entered.  The value returned is _DASTEPSTATE after all the variables
have been entered.

daentervar(j1 [,j2, ...], silent:T) and daentervar(varname1 [,varname2,
...], silent:T) do the same, except no report is printed.  This would
normally be followed by dastepstatus() to print a report after all the
variables have been entered.

See also dastepstatus(), daremovevar()  and dasteplook().

Gary Oehlert 2003-01-15