Oops, my bad.
I rarely do regression, so I forgot that in your case the explaining
variables do not have to be factors.
The rest stands.
Ivan
Le 10/12/2010 11:56, Ivan Calandra a écrit :
Hi,
Your response (dependent) variable, which has to be on the left side
of the '~' in the formula, should be numeric. In your example deny is
a factor; first problem
The explaining variables, on the right side of the '~', should be
factors. Here, hir, dir, css and mcs are numeric; second problem. Only
black is a factor.
There are two possibilities (not mutually exclusive):
- you should transform your factors into numeric and vice-versa as
needed, see ?factor and ?as.numeric, as well as StringAsFactor
argument from ?read.table (I guess you imported your data.frame that way)
- you should adjust your model formula. It might be that you mixed up
the variables in the formula. See ?formula
HTH,
Ivan
Le 10/12/2010 11:39, Gabriel Bergin a écrit :
Hi,
I am trying to do a multiple regression on the dataset "Hdma",
available in
the Ecdat package.
The data looks like this:
str(Hdma)
'data.frame': 2381 obs. of 13 variables:
$ dir : num 0.221 0.265 0.372 0.32 0.36 ...
$ hir : num 0.221 0.265 0.248 0.25 0.35 ...
$ lvr : num 0.8 0.922 0.92 0.86 0.6 ...
$ ccs : num 5 2 1 1 1 1 1 2 2 2 ...
$ mcs : num 2 2 2 2 1 1 2 2 2 1 ...
$ pbcr : Factor w/ 2 levels "no","yes": 1 1 1 1 1 1 1 1 1 1 ...
$ dmi : Factor w/ 2 levels "no","yes": 1 1 1 1 1 1 1 1 2 1 ...
$ self : Factor w/ 2 levels "no","yes": 1 1 1 1 1 1 1 1 1 1 ...
$ single : Factor w/ 2 levels "no","yes": 1 2 1 1 1 1 2 1 1 2 ...
$ uria : num 3.9 3.2 3.2 4.3 3.2 ...
$ comdominiom: num 0 0 0 0 0 0 1 0 0 0 ...
$ black : Factor w/ 2 levels "no","yes": 1 1 1 1 1 1 1 1 1 1 ...
$ deny : Factor w/ 2 levels "no","yes": 1 1 1 1 1 1 1 1 2 1 ...
I would like to try a more complex regression, but even this relatively
uncomplicated one returns an error:
summary(lm(deny ~ hir + dir + ccs + mcs + black))
The error I get is:
Error in storage.mode(y)<- "double" :
invalid to change the storage mode of a factor
In addition: Warning message:
In model.response(mf, "numeric") :
using type="numeric" with a factor response will be ignored
I understand that there is something wrong due to the fact that some
of the
variables are factors. But as far as I've grasped, it should be
possible to
include factor variables when using lm(). Am I in error in thinking
this?
Sincerely,
Gabriel Bergin
Undergraduate economics student
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