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### When to remove insignificant variables?

I'm working on logistic regression model. I checked the summary of the model which is built on 5 independent variables out which one is not significant with a P-value of 0.74.I wish to know that do we ...
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### Problem understanding the logistic regression link function

I am trying to learn the logistic regression model. I came to know that there is no linear relationship between predictor variables and response variables since response variables are binary (...
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### Why significant variable doesn't improve model performance?

I have a binary classification problem with 5K records and 60+ features/columns/variables. dataset is slightly imbalanced (or not) with 33:67 class proportion What I did was 1st) Run a logistic ...
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### Why is logistic regression well calibrated, and how to ruin its calibration?

In the scikit learn documents on probability calibration they compare logistic regression with other methods and remark that random forest is less well calibrated than logistic regression. Why is ...
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### How should two cross-validated logistic regression models be compared?

I'm using 100 times 10-fold repeated cross-validation to assess the ROC-AUC performance improvement of adding a biomarker to an existing model: Model_A : pred1 + pred2 Model_B :pred1 + pred2 + pred3 I'...
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1 vote
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### R - Model selection in Glmer

Having troubles to perform a model selection for glmer in R. I'm using the package lme4 with the following structure: ...
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### Probability threshold in ROC curve analyses

When conducting a logistic regression analysis in SPSS, a default threshold of 0.5 is used for the classification table. Consequently, individuals with a predicted probability < 0.5 are assigned to ...
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### Importance of C statistic in logistic regression

I am working on a dataset with 1500 cancer patients. The research question is impact of various patient and surgery related variables on disease specific mortality. So the outcome/dependent variable ...