Hello,
Inline.
Às 20:01 de 01/08/2020, John Fox escreveu:
Dear Paul,
I think that this thread has gotten unnecessarily complicated. The
answer, as is easily demonstrated, is that a binary response for a
binomial GLM in glm() may be a factor, a numeric variable, or a
logical variable, with identical results; for example:
--------------- snip -------------
> set.seed(123)
> head(x <- rnorm(100))
[1] -0.56047565 -0.23017749 1.55870831 0.07050839 0.12928774
1.71506499
> head(y <- rbinom(100, 1, 1/(1 + exp(-x))))
[1] 0 1 1 1 1 0
> head(yf <- as.factor(y))
[1] 0 1 1 1 1 0
Levels: 0 1
> head(yl <- y == 1)
[1] FALSE TRUE TRUE TRUE TRUE FALSE
> glm(y ~ x, family=binomial)
Call: glm(formula = y ~ x, family = binomial)
Coefficients:
(Intercept) x
0.3995 1.1670
Degrees of Freedom: 99 Total (i.e. Null); 98 Residual
Null Deviance: 134.6
Residual Deviance: 114.9 AIC: 118.9
> glm(yf ~ x, family=binomial)
Call: glm(formula = yf ~ x, family = binomial)
Coefficients:
(Intercept) x
0.3995 1.1670
Degrees of Freedom: 99 Total (i.e. Null); 98 Residual
Null Deviance: 134.6
Residual Deviance: 114.9 AIC: 118.9
> glm(yl ~ x, family=binomial)
Call: glm(formula = yl ~ x, family = binomial)
Coefficients:
(Intercept) x
0.3995 1.1670
Degrees of Freedom: 99 Total (i.e. Null); 98 Residual
Null Deviance: 134.6
Residual Deviance: 114.9 AIC: 118.9
--------------- snip -------------
The original poster claimed to have encountered an error with a 0/1
numeric response, but didn't show any data or even a command. I
suspect that the response was a character variable, but of course
can't really know that.
So continuing with your example:
> head(yc <- as.character(y))
[1] "0" "1" "1" "1" "1" "0"
> glm(yc ~ x, family=binomial)
Error in weights * y : non-numeric argument to binary operator
But the OP says that
[...] R complains that I should make the dependent variable a factor.
That is not what the error message says, it "asks" for a numeric
argument to the '*' operator.
We haven't seen the exact R message yet, so, like others have said, the
OP should post it along with code.
Hope this helps,
Rui Barradas
Best,
John
John Fox, Professor Emeritus
McMaster University
Hamilton, Ontario, Canada
web: https://socialsciences.mcmaster.ca/jfox/
On 2020-08-01 2:25 p.m., Paul Bernal wrote:
Dear friend,
I am aware that I have a binomial dependent variable, which is covid
status
(1 if covid positive, and 0 otherwise).
My question was if R requires to turn a binomial response variable
into a
factor or not, that's all.
Cheers,
Paul
El sáb., 1 de agosto de 2020 1:22 p. m., Bert Gunter
<bgunter.4...@gmail.com>
escribió:
... yes, but so does lm() for a categorical **INdependent** variable
with
more than 2 numerically labeled levels. n levels = (n-1) df for a
categorical covariate, but 1 for a continuous one (unless more complex
models are explicitly specified of course). As I said, the OP seems
confused about whether he is referring to the response or
covariates. Or
maybe he just made the same typo I did.
Bert Gunter
"The trouble with having an open mind is that people keep coming
along and
sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On Sat, Aug 1, 2020 at 11:15 AM Patrick (Malone Quantitative) <
mal...@malonequantitative.com> wrote:
No, R does not. glm() does in order to do logistic regression.
On Sat, Aug 1, 2020 at 2:11 PM Paul Bernal <paulberna...@gmail.com>
wrote:
Hi Bert,
Thank you for the kind reply.
But what if I don't turn the variable into a factor. Let's say
that in
excel I just coded the variable as 1s and 0s and just imported the
dataset
into R and fitted the logistic regression without turning any
categorical
variable or dummy variable into a factor?
Does R requires every dummy variable to be treated as a factor?
Best regards,
Paul
El sáb., 1 de agosto de 2020 12:59 p. m., Bert Gunter <
bgunter.4...@gmail.com> escribió:
x <- factor(0:1)
x <- factor("yes","no")
will produce identical results up to labeling.
Bert Gunter
"The trouble with having an open mind is that people keep coming
along
and
sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On Sat, Aug 1, 2020 at 10:40 AM Paul Bernal <paulberna...@gmail.com>
wrote:
Dear friends,
Hope you are doing great. I want to fit a logistic regression in R,
where
the dependent variable is the covid status (I used 1 for covid
positives,
and 0 for covid negatives), but when I ran the glm, R complains
that I
should make the dependent variable a factor.
What would be more advisable, to keep the dependent variable
with 1s
and
0s, or code it as yes/no and then make it a factor?
Any guidance will be greatly appreciated,
Best regards,
Paul
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--
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NEW Service Models: http://malonequantitative.com
He/Him/His
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