13 questions linked to/from Backward selection for Cox model using R
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### Algorithms for automatic model selection

I would like to implement an algorithm for automatic model selection. I am thinking of doing stepwise regression but anything will do (it has to be based on linear regressions though). My problem ...
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### Stepwise regression in R - How does it work?

I am trying to understand the basic difference between stepwise and backward regression in R using the step function. For stepwise regression I used the following command ...
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### Should I remove non-significant variables from my regression model

I have run a multiple linear regression using stepwise regression to select the best model, however the best model returned has a non-significant variable. When I remove this the AIC value goes up ...
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### Forward or backward sequential feature selection?

I was trying to carry out feature selection on a dataset using sequential feature selection. The dataset contains more than 5000 observations (rows) and 22 features (columns). Now I see that there are ...
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### Combining principal component regression and stepwise regression

I want to use a combination of principal component analysis (PCA) and stepwise regression to develop a predictor model. I have 5 independent variables (which are correlated among each other to ...
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### Investigating interaction

Please I need to check for interaction before building an explanatory model (logistic regression). I have 16 interaction terms in total. Please how what is the best way to go about it. Will I need to ...
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### F-statistics based method out of fashion?

I'm reading Elements of Statistical Learning and come across this paragraph right before section 3.3.3: Other more traditional packages base the selection on F -statistics, adding “significant” ...
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### Feature Selection in unbalanced data

I was always taught 3 things: Training algorithms (rf, trees, etc) don't perform well with unbalanced data. I should balance data only after performing feature selection (mainly to keep variables ...
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### Should I report the pseudo $R^2$ value for full or final logistic regression model after removing NA's & running stepwise selection?

I'm working with a logistic regression model in r. model <- glm(response~., family="binomial", data) and I'm using ...
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### Eliminate Qualitative Predictors (working in R)

So I'm a totally newbie to the field of statistics. I'm working on a project where I have a quantitative dependent variable that I'm supposed to predict using a mixture between quantitive and ...
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### Understanding regression modelling: 3 factors, 3 continuous predictors

I am a bit confused about how regression modelling works. I have a response $y$, 3 continuous predictors, and 3 factors. I don't have anything else available. I fit the model ...