# Questions tagged [vif]

Variance Inflation Factor (VIF) quantifies the severity of multicollinearity in an ordinary least squares regression analysis. It provides an index that measures how much the variance (the square of the estimate's standard deviation) of an estimated regression coefficient is increased because of collinearity.

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### Why is multicollinearity not checked in modern statistics/machine learning

In traditional statistics, while building a model, we check for multicollinearity using methods such as estimates of the variance inflation factor (VIF), but in machine learning, we instead use ...
30k views

### Which variance inflation factor should I be using: $\text{GVIF}$ or $\text{GVIF}^{1/(2\cdot\text{df})}$?

I'm trying to interpret variance inflation factors using the vif function in the R package car. The function prints both a ...
7k views

### Collinearity diagnostics problematic only when the interaction term is included

I've run a regression on U.S. counties, and am checking for collinearity in my 'independent' variables. Belsley, Kuh, and Welsch's Regression Diagnostics suggests looking at the Condition Index and ...
27k views

### VIF, condition Index and eigenvalues

I am currently assessing multicollinearity in my datasets. What threshold values of VIF and condition index below/above suggest a problem? VIF: I have heard that VIF $\geq 10$ is a problem. After ...
8k views

### Multicollinearity when individual regressions are significant, but VIFs are low

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. ...
824 views

### What are the merits of different approaches to detecting collinearity?

I want to detect whether collinearity is a problem in my OLS regression. I understand that variance inflation factors and the condition index are two commonly used measures, but am finding it ...
1k views

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### Multicollinearity between ln(x) and ln(x)^2

I am running a negative binomial model and one of my predictor variables is a count variable. Since this variable was heavily skewed, I decided to log-transform it. However, the effect of this ...
3k views

### What is the fastest method for determining collinearity degree?

Given a large amount of data, how would I determine the degree of collinearity between all the variables? Preferably without relying on calculating linear regression between a variable and every other ...
135 views

### Why aren't we simply using $R_j^2$ instead the VIF?

After all we calculate the VIF by $1/(1-R_j^2)$. A VIF of $5$ corresponds to an $R_J^2$ of $0.8$. To me, the information given by $R_j^2$ just becomes more obscure when I apply the VIF formula. Why ...
7k views

### Is centering a valid solution for multicollinearity?

Let's assume that $y = a + a_1x_1 + a_2x_2 + a_3x_3 + e$ where $x_1$ and $x_2$ both are indexes both range from $0-10$ where $0$ is the minimum and $10$ is the maximum. I found by applying VIF, CI and ...
14k views

### How to interpret R VIF function in CAR package?

I am using the vif function in the R package car to test for multicollinearity. I am a little confused at the output given. For example, I have 5 variables (x1, x2, ...
11k views

### VIF for generalized linear model

Is the variance inflation factor useful for GLM models. Below example shows OLS is showing VIF>5, but GLM lower. GLM shows instability in the coefficients between train and test set. ...
43k views

### How to interpret a VIF of 4?

I am doing a multiple regression, trying to test the extent to which personal income changes and Presidential popularity can predict election results. I have a small sample size, unfortunately, as ...
675 views

### At what VIF level should you switch from OLS to ridge-regression?

Regarding multicollinearity, is it recommended to use ridge-regression if you have some covariates with VIF values around 10 in the OLS model? What would be the best VIF level to use to decide ...
10k views

### How to test for multicollinearity among dummy explanatory variables?

I have a Box-Cox regression where the explanatory variables are almost all dummy variables. If I want to see if there is multicollinearity among them, what would be an appropriate test? Do variance ...
576 views

### Variance Inflation Factor less than 1 in ridge regression?

I was trying to determine the biasing constant in ridge regression when I came across a phenomenon that seems quite puzzling, to me at least. I let the GCV criterion choose a constant for me and then ...
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### VIF calculation in regression

I want to use VIF to check the multicollinearity between some ordinal variables and continuous variables. When I put one variable as dependent and the other as independent, the regression gives one ...
495 views

### variable reduction before doing random forest in R

I have a dataset featuring around 50 predictors, some of which are correlated. Now I am trying to fit a random forest model in R for prediction purpose with this dataset. Because there are too many ...
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### Does the VIF make sense for a model with categorical variables?

I'm trying to detect multicollinearity in my model, it has count response variable and some proportional and one categorical explanatory variable called site. In R the model looks like this: ...
628 views

### VIF values in regression

Do high VIF values for a a particular variable $x$ just indicate that it is highly correlated with at least one of the other variables in the model? Does it specify which variables and how many ...
572 views

### VIF Drops Significantly When I Delete Some Dummy Variables

Is my model valid even with the high VIF? Does it matter which dummy variable I drop as the reference point? I have a a category variable (Fruit) that I converted ...
10k views

### VIF values and interactions in multiple regression

I am running a multiple regression of the form y~a+b+c+ab+ac+bc I have checked the VIF values for the direct effects - should I check them for the interactions? I am assuming not as that would ...
546 views

### VIF understanding - does only >4 variables are multi-collinear and others are not?

I am trying to understand if there will be multicollinearity between few variables or not. I took a sample data and tried to see the Variance Influencing Factor results - in general vif > 4 indicates ...
581 views

### Multicollinearity Using VIF and Condition Indeces

I am testing my dataset for multicollinearity using VIF and condition indices(CI).My dataset is cross-sectional macroeconomics data. I have 6 independent variables ($x_1$,$x_2$,$x_3$,$x_4$,$x_5$,$x_6$)...
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### Multicollinearity: How to convert GVIF^(1/(2df)) values to VIF

I am using the GVIF^(1/(2df)) method in my analyses to check for multicollinearity of my (mainly) categorical variables. However, I am struggling with the cut-off values. For the 'regular' VIF several ...
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### Identical VIF/Tolerance scores - Multiple regression

To begin - I am extremely bad at stats. I am running a multiple regression analysis on a dataset to predict one variable from two others. There were three independent variables(IV) before, although I ...