Open links in new tab
  1. Statistics by Jim
    https://statisticsbyjim.com › regression › variance-inflation-factors

    Variance Inflation Factors (VIFs) - Statistics By Jim

    • Multicollinearity is correlation amongst the independent variables. Consequently, it seems logical to assess the pairwise correlation between all independent variables (IVs) in the model. That is … See more

    Calculating Variance Inflation Factors

    VIFs use multiple regression to calculate the degree of multicollinearity. Imagine you have four independent variables: X1, X2, X3, and X4. Of course, the model has a dependent … See more

    Statistics by Jim
    How to Interpret Vifs

    From the above, we know that a VIF of 1 represents no multicollinearity, and … See more

    Statistics by Jim
    How to Calculate Vifs

    In my blog post about multicollinearity, I use regression analysis to model the relationship between the independent variables (physical activity, body fat percentage… See more

    Statistics by Jim
    How High Is Too High?

    A moderate amount of multicollinearity is okay. However, as multicollinearity increases, its effects also increase. What VIF values represent too much correlation? I’ve seen di… See more

    Statistics by Jim
    Feedback
    Table of Contents
    Calculating Variance Inflation Factors
    How to Interpret Vifs
    How to Calculate Vifs
    How High Is Too High?
     
  1. Variance inflation factor
    • According to 3 sources
    In statistics, the variance inflation factor (VIF) is the ratio (quotient) of the variance of a parameter estimate when fitting a full model that includes other parameters to the variance of the parameter estimate if the model is fit with only the parameter on its own.

    Variance inflation factor - …

    en.wikipedia.org
    The Variance Inflation Factor is a statistical measure used to assess the severity of multicollinearity in a regression analysis. It quantifies how much the variance of an estimated regression coefficient increases when your predictors are correlated.

    What is the Variance Inflati…

    databasecamp.de
    The variance inflation factor (VIF) quantifies the extent of correlation between one predictor and the other predictors in a model. It is used for diagnosing collinearity/multicollinearity. Higher values signify that it is difficult to impossible to assess accurately the contribution of predictors to a model.

    What are Variance Inflatio…

    displayr.com
  2. People also ask
    What does Vif mean in regression analysis?
    VIF measures the strength of the correlation between the independent variables in regression analysis. This correlation is known as multicollinearity, which can cause problems for regression models. While a moderate amount of multicollinearity is acceptable in a regression model, a higher multicollinearity can be a cause for concern.

    Variance Inflation Factor (VIF) - Investopedia

    investopedia.com
    What does a Vif of 1 mean?
    A VIF of 1 means that there is no correlation among the jth predictor and the remaining predictor variables, and hence the variance of bj is not inflated at all. The general rule of thumb is that VIFs exceeding 4 warrant further investigation, while VIFs exceeding 10 are signs of serious multicollinearity requiring correction.

    10.7 - Detecting Multicollinearity Using Variance Inflation Factors

    online.stat.psu.edu
    What is the upper limit of a Vif?
    The value for VIF starts at 1 and has no upper limit. A general rule of thumb for interpreting VIFs is as follows: A value of 1 indicates there is no correlation between a given predictor variable and any other predictor variables in the model.

    How to Calculate Variance Inflation Factor (VIF) in R - Statology

    statology.org
    How do you calculate Vif?
    It measures how much the variance (or standard error) of the estimated regression coefficient is inflated due to collinearity. VIF can be calculated by the formula below: Where Ri2 represents the unadjusted coefficient of determination for regressing the i th independent variable on the remaining ones. The reciprocal of VIF is known as tolerance.

    Variance Inflation Factor (VIF) - Overview, Formula, Uses

    corporatefinanceinstitute.com
    When is Vif greater than 1?
    By contrast, the VIF is greater than 1 when the vector Xj is not orthogonal to all columns of the design matrix for the regression of Xj on the other covariates. Finally, note that the VIF is invariant to the scaling of the variables (that is, we could scale each variable Xj by a constant cj without changing the VIF). Then we have,

    Variance inflation factor - Wikipedia

    en.wikipedia.org
    What happens if Vif is higher than 10?
    When VIF is higher than 10, there is significant multicollinearity that needs to be corrected. For example, suppose that an economist wants to test whether there is a statistically significant relationship between the unemployment rate (independent variable) and the inflation rate (dependent variable).

    Variance Inflation Factor (VIF) - Investopedia

    investopedia.com
    Feedback
  3. Statistics How To
    https://www.statisticshowto.com › variance-in

    Variance Inflation Factor - Statistics How To

  4. Statology
    https://www.statology.org › multicollinearity-regression

    A Guide to Multicollinearity & VIF in Regression - Statology

  5. Investopedia
    https://www.investopedia.com › terms …

    Variance Inflation Factor (VIF) - Investopedia

    Jun 27, 2024 · A variance inflation factor (VIF) is a measure of the amount of multicollinearity in regression analysis. Multicollinearity exists when there is a correlation between multiple independent...

  6. Corporate Finance Institute
    https://corporatefinanceinstitute.com › re…

    Variance Inflation Factor (VIF) - Overview, Formula, Uses

    Up to3.2%cash back
     · What is the Variance Inflation Factor (VIF)? The Variance Inflation Factor (VIF) measures the severity of multicollinearity in regression analysis. It is a statistical concept that indicates the increase in the …

  7. Statology
    https://www.statology.org › variance-infl…

    How to Calculate Variance Inflation Factor (VIF) in R

    May 9, 2019 · The most common way to detect multicollinearity is by using the variance inflation factor (VIF), which measures the correlation and strength of correlation between the predictor variables in a regression model.

  8. Medium
    https://medium.com

    Understanding VIF: What It Is and Why It’s Needed

  9. Pennsylvania State University
    https://online.stat.psu.edu › node

    10.7 - Detecting Multicollinearity Using Variance …

    As the name suggests, a variance inflation factor (VIF) quantifies how much the variance is inflated. But what variance? Recall that we learned previously that the standard errors — and hence the variances — of the estimated coefficients …

  10. Statlect
    https://www.statlect.com › ... › variance …

    Variance inflation factor | Computation, derivation, …

    Learn how the variance inflation factor (VIF) is defined, and how it is derived and calculated. Understand under what assumptions the VIF provides reliable indications.