Linked Questions

My study is a prospective observational study. My dependent variable (outcome) is development of surgical site infection (SSI) after surgery and my independent variables (predictors) are many factors ...

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 ...

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 ...

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 ...

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 ...

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 ...

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. ...

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.. ...

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 ...

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 ...

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 ...

So I have a full model such as; ...

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 ...

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 ...

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 ...