Methodology
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General approach
Regression
Using logistic regression for classification problems
Survival modeling
Data scrubbing
Outliers
Predictive variable selection
Removing highly correlated variables
Computing a univariate odds ratio
Computing a multivariate odds ratio
Assessing model coefficients
Transformation of variables
Including interaction terms in the model
Model validation
Linear regression
Logistic regression
Validation of temporal datasets
Predicting future outcomes
Evaluating model performance
Receiver operating characteristics curve
Summary of model performance metrics
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