# Linked Questions

299 questions linked to/from Algorithms for automatic model selection
1answer
3k views

### 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 ...
0answers
667 views

### 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 ...
1answer
665 views

### 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 ...
0answers
598 views

### 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 ...
0answers
262 views

### 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. ...
1answer
82 views

### 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 ...
1answer
138 views

### 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.. ...
1answer
80 views

### 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 ...
0answers
70 views

### 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 ...
1answer
20 views

### Is forward selection using AIC as selection critiria valid? [duplicate]

I'm using a sequential approach to decide the best fitting model for my data. (I'm still new to R, so I decided to go for a manual approach rather than an automated one offered by R packages). I'm ...
0answers
19 views

### Using stepAIC to help select final model [duplicate]

So I have a full model such as; ...
0answers
17 views

### Why is the use of the F-Statistic / p-value as a criteria in Stepwise Model Selection outdated? [duplicate]

I am coming from the field of psychology and in most publications Model Selection (OLS, Regression) is done via Forward/Backward Selection using the F-Static/p-value of the regression coefficients to ...
7answers
119k views

### 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 ...
3answers
9k views

### 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-...
1answer
25k views

### What is an ablation study? And is there a systematic way to perform it?

What is an ablation study? And is there a systematic way to perform it? For example, I have $n$ predictors in a linear regression which I will call as my model. How will I perform an ablation study ...

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