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.
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
[[alternative HTML version deleted]]
______________________________________________
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
[[alternative HTML version deleted]]
______________________________________________
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
--
Patrick S. Malone, Ph.D., Malone Quantitative
NEW Service Models: http://malonequantitative.com
He/Him/His
[[alternative HTML version deleted]]
______________________________________________
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
______________________________________________
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
