Linked Questions

5
votes
1answer
9k views

Difference between effect size (partial $R^2$) and coefficients [duplicate]

I am working with spoken language data and use linear models do determine the relationship between different phonological processes in my data. Background Measures of the regularity of syllable ...
45
votes
3answers
68k views

Suppression effect in regression: definition and visual explanation/depiction

What is a suppressor variable in multiple regression and what might be the ways to display suppression effect visually (its mechanics or its evidence in results)? I'd like to invite everybody who has ...
17
votes
3answers
12k views

For linear classifiers, do larger coefficients imply more important features?

I'm a software engineer working on machine learning. From my understanding, linear regression (such as OLS) and linear classification (such as logistic regression and SVM) make a prediction based on ...
38
votes
2answers
51k views

Multiple regression or partial correlation coefficient? And relations between the two

I don't even know if this question makes sense, but what is the difference between multiple regression and partial correlation (apart from the obvious differences between correlation and regression, ...
14
votes
2answers
10k views

Why can't ridge regression provide better interpretability than LASSO?

I already have an idea about pros and cons of ridge regression and the LASSO. For the LASSO, L1 penalty term will yield a sparse coefficient vector, which can be viewed as a feature selection method. ...
13
votes
1answer
7k views

Should partial $R^2$ add up to total $R^2$ in multiple regression?

Following is a model created from mtcars dataset: ...
4
votes
1answer
12k views

How to evaluate effect size from a regression output

When running a regression, statistical significance of an effect is important but its magnitude is even more important. How should I evaluate the size of an effect? I've read that usually in ...
4
votes
1answer
4k views

Which variable relative importance method to use?

Following is a plot from relaimpo package of R which shows relative importance of predictor variables for regression of mpg on all other variables in mtcars dataset. The relative importance is ...
3
votes
1answer
313 views

Which are the most important predictors (and how great is their impact) of a continuous dependent variable?

I have a continuous outcome (dependent) variable, which is body weight and I'm wondering which of my 20 candidate predictors (independent variables) are the most important ones for prediting body ...
1
vote
0answers
807 views

How to partition $R^2$ among predictors in multiple regression with interaction terms in R

Say I have some predictors, and I know how they affect some dependent variable: ...
1
vote
0answers
110 views

relaimpo output interpretation and relationship to the coefficients outputs in linear regression

I come accross the relaimpo package in R with the hope of using it to assess the importance of the regressors in a linear regression problem. I am interested in understanding how to relate the output ...
1
vote
1answer
48 views

SPSS - Automatic Linear Modeling “Importance” Numbers

I have a large set of survey data. I'm looking at trying to find out which variables are the most important to impacting a DV (call it "happiness"). I'm not looking to find a beta number ...