Jun 30, 2023 · In this forum, there are opposite opinions(1), (2) on the uses of logistic regression. Ones say, it is a classification model and others say it is a prediction model. Therefore, the question that I...

In my book Regression Modeling Strategies I downplay the use of residuals in logistic regression because (1) logistic regression makes no distributional assumptions and (2) there are more direct …

Feb 1, 2024 · I am struggling to decide which reference category I should define in my logistic regression model. When I define "mandatory school" as a reference in the variable …

This one is good for capturing things like ambiversion. Logistic regression works with both - continuous variables and categorical (encoded as dummy variables), so you can directly run logistic regression …

Logistic regression is a special case of this binomial/binary regression and it is the logistic link function that has the asymptotic nature. In addition the 'overfitting' is mostly problematic for cases with perfect …

Mar 3, 2014 · I want to know why logistic regression is called a linear model. It uses a sigmoid function, which is not linear. So why is logistic regression a linear model?

Oct 18, 2022 · I ran a logistic regression model in R and then wanted to calculate the predicted probability for my two independent variables. My dependent variable (DV) is binary (0,1). I used the …

Jul 2, 2018 · I'm using a binomial logistic regression to identify if exposure to has_x or has_y impacts the likelihood that a user will click on something. My model is the following: fit = glm (formula = has_cli...

Jan 14, 2021 · I have built a logistic regression model which takes a dataframe of dummy values as an input and produces binary classification (0 for accept, 1 for default). I have already split all variables …

Dec 25, 2016 · 8 I would like to assess the goodness of fit of a logistic regression model I'm working on. I've done a lot of research and happened to find likelihood ratio test, chi-squared test, Hosmer and …