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...

Sep 20, 2023 · 3 I'm keen to know how to compute the variance explained by a particular predictor variable in the model (say component specific R squared). I went through Calculate variance …

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 …

Jan 26, 2022 · The calibrate function in the rms R package allows us to compare the probability values predicted by a logistic regression model to the true probability values. This is easy enough: just plot …

Is it possible to conduct a regression if all dependent and independent variables are categorical variables?

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?

Logistic regression is neither linear nor is it a classifier. The idea of a "decision boundary" has little to do with logistic regression, which is instead a direct probability estimation method that separates …

Mar 26, 2016 · It is the exact opposite actually - statsmodels does not include the intercept by default. See the SO threads Coefficients for Logistic Regression scikit-learn vs statsmodels and scikit-learn & …

Oct 17, 2014 · For example, some people would say they're the same, but other people would use "logistic function" (and hence sometimes even 'a logistic regression') to refer to a nonlinear …

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...