Greetings,
I want to compare the goodness-of-fit between several different models that
I have developed using Logistic Regression. I have been doing some research
and am sort of confused on how to do this. I know it is not as simple as in
an OLS model, however since there is no "R-squared" valu
I am very very new with R.
Needless to say, your comment is a bit confusing. My regression name is
"mylogit"
Anyway to write a code that I can copy paste? Thanks
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EstimateStd. Error z value
Pr(>|z|)
(Intercept) 2.338e+00
2.400e+03 0.0010.99922
fac
I want to export the coefficient values and p-values from my regression
output into a spreadsheet. Is there a way to do this?
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I do not see an R-squared value after preforming the glm regression.
Is there a separate command for this?
Thanks
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I am very new to R, so I apologize if this question is trivial.
I have a row in my data of dates in the format mm/dd/; about 3500 rows.
I am using this variable in a logistic regression model, and need to treat
it as continuous, not a factor as r has decided it is.
I tried the as.numeric fu
How to change categorical vars to factors.
I am very new at R
Thanks
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_
I have a rather large data set (about 30 predictor variables)
I need to preform a logistic regression on this data. My response variable
is binary.
My code looks like this:
mylogit <- glm(Enrolled ~ A + B + C + ... + EE, data = data, family =
binomial(link="logit"))
with A,B,C, ... as my predic
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