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...

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 …

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 …

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 …

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?

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 …

Standardization isn't required for logistic regression. The main goal of standardizing features is to help convergence of the technique used for optimization. For example, if you use Newton-Raphson to …

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...

Mar 27, 2015 · What is the difference between Logit and Probit model? I'm more interested here in knowing when to use logistic regression, and when to use Probit. If there is any literature which …