Re: [R] Dependent Variable in Logistic Regression
I like using a logical response in cases like this, but put its
construction in the formula so it is unambiguous when I look at the
results later.
> d <- data.frame(Covid=c("Pos","Pos","Neg","Pos","Neg","Neg"), Age=41:46)
> glm(family=binomial, data=d, Covid=="Pos"~Age)
Call: glm(formula = Covid == "Pos" ~ Age, family = binomial, data = d)
Coefficients:
(Intercept) Age
52.810 -1.214
Degrees of Freedom: 5 Total (i.e. Null); 4 Residual
Null Deviance: 8.318
Residual Deviance: 4.956AIC: 8.956
Bill Dunlap
TIBCO Software
wdunlap tibco.com
On Sat, Aug 1, 2020 at 12:21 PM John Fox wrote:
>
> 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: 114.9AIC: 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: 114.9AIC: 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: 114.9AIC: 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
> >
> > 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
> >>> 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
> > wrote:
> >
> >> Dear friends,
> >>
> >>
Re: [R] Dependent Variable in Logistic Regression
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
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
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
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
Re: [R] Dependent Variable in Logistic Regression
I didn't mean to imply that was the only time that it was required, only
that it's not universal in R.
On Sat, Aug 1, 2020 at 2:22 PM Bert Gunter wrote:
> ... 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
>> 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
>>> > 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
>>
>
--
Patrick S. Malone, Ph.D., Malone Quantitative
NEW Service Models: http://malonequantitative.com
He/Him/His
[[alternative HTML version deleted]]
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and provide commented, minimal, self-contained, reproducible code.
Re: [R] Dependent Variable in Logistic Regression
Hello,
From the documentation, help('glm'):
Details
A typical predictor has the form|response ~ terms|where|response|is the
(numeric) response vector and|terms|is a series of terms which specifies
a linear predictor for|response|.
For|binomial|and|quasibinomial|families the response can also be
specified as a|factor
|(when the first level
denotes failure and all others success) or as a two-column matrix with
the columns giving the numbers of successes and failures. A terms
specification of the form|first + second|indicates all the terms
in|first|together with all the terms in|second|with any duplicates removed.
There is no need for the response to be a factor, it is optional, the
wording is very clear,
"For|binomial|and|quasibinomial|families the response *can* also be
specified as a|factor "|
And with binary, numeric responses I cannot reproduce the warning
message, the models fit silently.
Hope this helps,
Rui Barradas
Às 18:39 de 01/08/2020, Paul Bernal escreveu:
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]]
__
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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.
--
Este e-mail foi verificado em termos de vírus pelo software antivírus Avast.
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and provide commented, minimal, self-contained, reproducible code.
Re: [R] Dependent Variable in Logistic Regression
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: 114.9AIC: 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: 114.9AIC: 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: 114.9AIC: 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
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
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
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]]
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http://www.R-project.org/posting-guide.html
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[[alternative HTML version deleted]]
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http://www.R-project.org/posting-guide.html
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--
Patrick S. Malone, Ph.D.,
Re: [R] Dependent Variable in Logistic Regression
You appear to be confusing a binomial **response** with categorical
"dependent variables." glm() of course fits continuous or categorical
dependent variables. If a continuous dependent variable has only 2 values,
the results for glm() will be the same whether or not it is considered to
be continuous or categorical, though you may not recognize it as such.
This discussion has already wandered off topic to statistical issues. I
will not comment further on or off list. I suggest you consult a good
reference on linear/generalized linear models or talk with a local
statistician.
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 11:04 AM Paul Bernal 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
>> 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
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] Dependent Variable in Logistic Regression
No, R does not. glm() does in order to do logistic regression.
On Sat, Aug 1, 2020 at 2:11 PM Paul Bernal 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
> > 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]]
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Re: [R] Dependent Variable in Logistic Regression
... and further:
" If a continuous independent variable has only 2 values,..."
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 11:11 AM Bert Gunter wrote:
> You appear to be confusing a binomial **response** with categorical
> "dependent variables." glm() of course fits continuous or categorical
> dependent variables. If a continuous dependent variable has only 2 values,
> the results for glm() will be the same whether or not it is considered to
> be continuous or categorical, though you may not recognize it as such.
>
> This discussion has already wandered off topic to statistical issues. I
> will not comment further on or off list. I suggest you consult a good
> reference on linear/generalized linear models or talk with a local
> statistician.
>
> 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 11:04 AM Paul Bernal
> 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
>>> 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]]
__
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http://www.R-project.org/posting-guide.html
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>>>
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Re: [R] Dependent Variable in Logistic Regression
Sorry, typo.My first sentences should read:
"You appear to be confusing a binomial **response** with categorical
"independent variables." glm() of course fits continuous or categorical
independent variables."
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 11:11 AM Bert Gunter wrote:
> You appear to be confusing a binomial **response** with categorical
> "dependent variables." glm() of course fits continuous or categorical
> dependent variables. If a continuous dependent variable has only 2 values,
> the results for glm() will be the same whether or not it is considered to
> be continuous or categorical, though you may not recognize it as such.
>
> This discussion has already wandered off topic to statistical issues. I
> will not comment further on or off list. I suggest you consult a good
> reference on linear/generalized linear models or talk with a local
> statistician.
>
> 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 11:04 AM Paul Bernal
> 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
>>> 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]]
__
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PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
>>>
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Re: [R] Dependent Variable in Logistic Regression
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
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
>> 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
>>> > 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]]
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] Dependent Variable in Logistic Regression
... 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 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
>> > 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]]
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] Dependent Variable in Logistic Regression
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
> 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]]
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and provide commented, minimal, self-contained, reproducible code.
Re: [R] Dependent Variable in Logistic Regression
On Sat, 1 Aug 2020, Paul Bernal wrote: 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? Paul, 1 or 0 are equivalent to yes or no, success or failure. All are nomminal variables so all should be factors, regardless of the coding. Rich __ 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.
Re: [R] Dependent Variable in Logistic Regression
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 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]]
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
[R] Dependent Variable in Logistic Regression
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.
