264 questions linked to/from Algorithms for automatic model selection
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### Main Drawbacks of stepwise regression [duplicate]

People typically prefer the Lasso or other methods to stepwise regression. What are the main problems in stepwise regression which makes it unreliable specifically the problems with forward selection ...
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### p-values for feature selection [duplicate]

I am doing multiple regression analysis, in which i want to eliminate some of the insignificant features. In most of the machine learning books subset selection, shrinkage methods or PCA is used for ...
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### Chi Square and t test to select variables for logistic regression [duplicate]

I need to build a logistic regression model. there are around 50 categorical variables. So, is this approach to select variables wrong?: do a chi square test of dependent variable vs independent ...
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### How to choose predictor variables for GLM / GLMM from rather large data set? [duplicate]

I have about 80 predictor variables (with some multicollinearity, I assume) and a non-normal count data response variable (n=570) which is arranged into groups (n=34). I need to reduce the number of ...
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### Why avoid stepwise regression? [duplicate]

I have been using model averaging and model selection bases on AIC and BIC for a while. I have recently discover the stepwise regression technique and I found a lots of people critize this methods. ...
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### Chi square and logistic regression [duplicate]

Before running a binary logistic regression model i was interested to know the strength of association between IV and DV but for some independent variables the results came out to be insignificant.. ...
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### In stepwise regression, how to interpret non-significant variables? [duplicate]

I have more than 15 IVs such as age, gender, education, first language, technology proficiency, health condition, etc, and one of my DVs is health literacy level, which is measured through a standard ...
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### Beginner - Iteratively adding terms to regression model? [duplicate]

I'm learning about regression models via Andrew Ng's Coursera course. I have a question regarding automatically finding a good model. Does it make sense (my guess is no) to iteratively add terms, or ...
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### Logistic Regression Model Selection Criteria [duplicate]

I'm having a go at coding a logistic regression model building algorithm and I'd appreciate some advice. I've read in several places (including here) that minimizing both AIC and BIC could be an ...
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### Is it possible to change a hypothesis to match observed data (aka fishing expedition) and avoid an increase in Type I errors?

It is well known that researchers should spend time observing and exploring existing data and research before forming a hypothesis and then collecting data to test that hypothesis (referring to null-...
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### Choosing variables to include in a multiple linear regression model

I am currently working to build a model using a multiple linear regression. After fiddling around with my model, I am unsure how to best determine which variables to keep and which to remove. My ...
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### A more definitive discussion of variable selection

Background I'm doing clinical research in medicine and have taken several statistics courses. I've never published a paper using linear/logistic regression and would like to do variable selection ...
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### Can I ignore coefficients for non-significant levels of factors in a linear model?

After seeking clarification about linear model coefficients over here I have a follow up question concerning non-signficant (high p value) for coefficients of factor levels. Example: If my linear ...
I have 6 variables ($x_{1}...x_{6}$) that I am using to predict $y$. When performing my data analysis, I first tried a multiple linear regression. From this, only two variables were significant. ...