# Search Results

Results tagged with Search options user 137921
8 results

Refers generally to statistical procedures that utilize the logistic function, most commonly various forms of logistic regression

I'm referring to this paper : Model building strategy for logistic regression: purposeful selection http://dx.doi.org/10.21037/atm.2016.02.15 Data is created at the start and I'm unsure about …
asked Dec 21 '18 by baxx
Context I'm not sure what to do in the scenario where one of the levels for a variable has so few levels that there's a good chance splitting the data into $70\%$ training $30\%$ testing will result …
to me how to justify the logistic model / curve. I have seen this post, this is not a question about whether or not binary logistic regression can be carried out using categorical predictors. What … I'm interested in is how to explain the use of the logistic curve in this model, as there doesn't seem to be a clear way like there is for a continuous predictor. edit data data that has been used …
After fitting a logistic regression model m I've run vif() on it and been given the following output GVIF Df GVIF^(1/(2*Df)) x1 6.040275 2 1.567704 x2 2.521120 …
question Given a table such as : $$\begin{array}{ll|ll} & A & {} \\ & & 0 & 1 \\ \hline B& 1 & 44 & 27 \\ &0 & 443 & 95 \end{array}$$ If I wanted to develop a logistic regression model …
variance. Could someone explain what this means in the context of logistic regression please. For example, suppose that the model was $$\log ( \text{odds} ) = \beta_0 + \beta_1 x_1$$ where \$x_1 …