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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1answer
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. ...
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1answer
265 views

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: ...
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1k views

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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420 views

In plain language, why is there no VIF for binary outcome regression models?

As far as I know, the variance inflation factor is not computed with pseudo-$R^{2}$ or generalized $R^{2}$ in binary outcome models (e.g. logistic regression). Are there other measures of multi-...
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171 views

Question about variance inflation factors

I'm considering the regression model $y_i = \beta_0 + \beta_1x_{1i} + \beta_2x_{2i} + \varepsilon_i$ where the $\varepsilon_i$ are iid and $\mathcal N(0,\sigma^2)$ A study question asks to show the ...
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0answers
45 views

Is multicolinearity testing altogether useless if the p-value on each regressor is less than 0.01?

Isn't the effect of multicolinearity to artificially increase the standard errors and thus artificially decrease the t-statistics, and thus artificially increase the p-values? If so, if all ...
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0answers
75 views

Is it appropriate to use a pseudo R-squared when calculating a variance inflation factor for a binary variable?

When calculating the Variance Inflation Factor for a variable $X_j$ in a multiple regression: $$VIF_j= \frac{1}{1-R^2_{j}}$$ if the variable in question is a dummy variable with 0/1 values, is it ...
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1k views

Multicollinearity (or not) in exploratory factor analysis

I’m performing an exploratory factor analysis with 28 items, n = 300. I’m confused whether I have a multicollinearity problem or not, and if so whether/how I go about choosing items to remove from the ...
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222 views

Identifying variables contributing to near multicollinearty in linear regression using VIF's and multiple R squared's

When trying to detect collinear columns in $X$ a high proportion of cases give a $R_k^2$ close to 1 for independent columns (see figure). When near multicollinearity arise in a $n\times m$ data ...
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153 views

VIF and coefficient variance-covariance matrix for OLS

After reading this answer, I am not very clear on how to get to the formula of VIF ($1/1-R^2$) as part of the variances on the diagonals of the variance-covariance matrix of the coefficients, if auto ...
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0answers
284 views

Should the intercept be included when you check the condition index?

Many sources state that a condition index >30 constitutes a multicollinearity problem. When I've tried to implement this check in practice, I've realized that the condition index (and VIFs) change ...
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56 views

How to show the equality of two Variance Inflation Factor(VIF) definitions

How to show the diagonal elements of the ${C = (X'X)^{-1}}$ are $C_{jj} = \frac{1}{1 - R_{j}^2}$ where $R_{j}^2$ is the coefficient of multiple determinations from the regression of $x_j$ on the ...
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60 views

Matrix singularity catch-22 in regression analysis

I'm trying to run a multiple regression, but I'm getting a singular matrix exception. I assume this means that there is high collinearity among my independent variables, so for each X I produce its ...
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0answers
274 views

VIF around 3.5 in two covariates, how shall I deal the problem?

in my multinomial logistic regression model (sample size n=290) I am adjusting the results for a group of covariates (n=8). I tested them for multicollinearity and if most of them have a VIF lower ...
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398 views

Multicolinearity in logistic regression using R

Upon performing binary logistic regression, I have found VIF, using R programming, as follows: ...
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739 views

Very low VIF values, but extreme high condition index

In my multiple linear regression model, all of my explanatory variables have a VIF score, lower then 3, but the highest condition index is 709. The constant and one of the explanatory variables have 1....
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0answers
11k views

VIF in GLM model in R

Before running or building a model, ho can we check on the multicollinearity between different covariates in GLM model in R? I know that SAS Proc MIXED procedure gives a column for VIF which is very ...
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282 views

What to do if a covariate is collinear in one model but not in another

I have 10 different species with presence/absences data, as well as 6 different covariates relating to the design of marinas, including 3 continuous (lengths of walls, pontoons and groynes) and 3 ...
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145 views

Understanding VIF procedure with different methods from r package rms and car - VIF by level of a factor

Consider the output from two different r packages, rms::vif and car::vif: ...
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40 views

VIF - Variance Inflation, when to remove the variable

I'm doing a regression analysis on cement mixtures. The goal is obviously to create the mixture with the most strength. Here are the following variables for me to work with: Variables: Strength = ...
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33 views

What regression diagnostics should I perform for an ordered probit?

Currently I have done the following diagnostics with the linktest multicollinearity with vif the parallel lines assumption with lr test of the oprobit and goprobit. I have seen that I may have to ...
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192 views

Using VIF in lasso does it make sense?

I tried to shrink all features that create multicollinearity problem in my model. For this I use VIF for understanding what level of $\alpha$ coefficient for lasso will be enough (calculate VIF for ...
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70 views

When is multicollinearity a good thing or acceptable?

I was looking through a few scenarios where it might be okay to use variables that have high VIF here. But most of such discussions and remedies I have seen use it in the context of linear regression ...
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86 views

How to deal with high VIF and multicollinearity between numerical and categorical values?

I'm performing a multiple linear regression about the price of alcohol. Two of the predictors are the categorical variable 'type of alcohol', the levels being 'beer', 'wine', 'spirits' and the ...
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111 views

Multicollinearity between predictors used to simulate data

I have simulated a dataset containing individual level variables that results from two processes. In the first process there is a selection of individuals according to one variable, say "indQual". ...
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0answers
1k views

What is the definition of the generalized variance inflation factors (GVIF)?

I am currently working on a statistical project at my school, in short, it is about finding the "best" linear regression model to explain the price of houses in a giving community. The model we have ...
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27 views

Does the estimation process in a regression effect multicollinearity tests

Does the applicability of VIF vary based on the parameter estimation process? For example, can I use VIF to check for multicollinearity if the parameters in my logistic regression are estimated using ...
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263 views

Variance Inflation Factors (VIFs) on model vs covariates themselves

I am confused on which type of "object" do the VIF functions operate. Let me give two examples, which are confusing me. The VIFs from the car and ...
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0answers
251 views

Why VIF is calculated on every value of a predictor in R?

I'm currently working on a logistic regression model and I wanted to pinpoint the VIF for every predictor inside the model. I've found that packages 'car' and 'HH' have the same vif function, so I ...
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0answers
182 views

Variance inflation factor

I am trying out VIF in order to reduce the number of variables, by removing highly collinear variables. I will be using VIF in R, but before applying it, does my time series need to be stationary?I ...
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0answers
329 views

feature seletion and multi-collinearity & vif

I want to use R to select a variable. In particular, variables are selected considering the correlation, and variables with large multicollinearity, which are correlations between variables, should be ...
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0answers
348 views

How to interpret differences in VIF and condition number?

In my present data, the Variance Inflation Factors suggest lack of substential multicolliniearity (<1,7). However, the condition number of 28 is almost at the critical value of 30. How do I ...
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0answers
29 views

Selecting Model Based On Data Set

I am doing a project for class in which we choose a data set and use SAS to analyze potential models to predict the response variable. I ran an preliminary proc reg in SAS to determine which variables ...
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257 views

Multicollinearity? Non-significant multiple-linear regression, highly correlated regressors but low variance inflation factor

I have a small sample (30 obs) and 4 independent variables, 3 of which are significantly correlated to each other. I have tried to run the simple linear regression on each of them separately and it ...
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0answers
222 views

Weeding out multi-collinear categorical variables

I have a huge amount of features that are categorical variables and I'm trying to find a system for weeding out categorical variables that are close to being multicollinear. Is vif a reasonable ...
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0answers
11 views

Usage of VIF in unsupervised model

I'm working on building an unsupervised model for real time anomaly detection based on the concept of Randomized Matrix Sketching (http://www.vldb.org/pvldb/vol9/p192-huang.pdf) which involves ...
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0answers
31 views

How to estimate the VIF for geeglm models in r

I am very new in r and at analyzing gee models. I have a very high dimensional data (51 independent variables measure at multiple times with no missing values (secondary dataset)). I am pretty sure ...
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0answers
16 views

Model Deviance lower than Residual Degree of Freedom

I am trying to calculate the Variance inflation factor (VIF) for a Generalized Additive Model (GAM). The GAM model contains both constant terms and splines. The VIF is defined as Deviance of model ...
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0answers
225 views

GVIF output in R

After fitting a logistic regression model m I've run vif() on it and been given the following output ...
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71 views

Variance inflation factors for time series

R code: I got an error by using vif function. ...
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0answers
310 views

Why is the value of vif from $(X'X)^{-1}$ not matching the result?

The diagonal elements of matrix $C = (X'X)^{-1}$ are $C_{jj} = \frac{1}{1-R_{j}^{2}}$ (which is nothing but the vif) of $x_j$ where $j = 1, 2, 3, ..., n$ and $X$ is a $n\times p$ matrix and $R_j^2$ ...
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0answers
23 views

Steps after calculating VIF to deal with multi collinearity

How do we eliminate variables after calculating VIF ? I have read about step wise removal of variables with high VIF till we reach VIF values below 5. On the other hand , my professor told me that ...
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0answers
325 views

Multicollinearity in the data with categorical variables

I want to calculate the vif to check for multicollinearity in my data set. I read that a values of >10 tells me that I could have a problem with multicollinearity in my data set. I run an ols ...
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0answers
123 views

How to test for multicollinearity over matrices?

I plan to test whether there is multicollinearity not between predictors in an individual linear regression model (columns in a matrix) but between the models (over matrices). The matrices are all ...
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0answers
46 views

GVIFs increase after removing variables

I have a qualitative dependent variable (Y), a dicothomic cathegorical variable (X1), a cathegorical variable (around 60 non-homogeneous groups, X2), two cathegorical variables (10-20 groups each, X3 ...
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0answers
79 views

lm in R: What's better? “ugly” model with high $R^2$ or a “beautiful” one with worse $R$? How much VIF is too much?

I have been trying to model with lm in R. I have several variables: Initial cell concentration $(X1)$, macroscopic appearance $(X2, X3, X4, X5)$, microscopic appearance $(X6,X7,X8)$, % of cells moving ...
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561 views

Should we run vif function right after glm() in R programming?

If not then where are we supposed to use that? If yes, then my vif values are all below 3, but statistically they are insignificant variables then what should I do next? How do I make myself ...
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0answers
3k views

Variation Inflation Factor Gives inf

I have a dataset that contains 292 attributes. I want to calculate VIF to address multicollinearity in dataset. Here is a snippet which I have used to calculate VIF ...
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0answers
1k views

Principal Components Analysis Regression VIF Interpretation in Minitab?

I'm trying to verify my understanding of how to apply principal component analysis to a multiple regression. Here's my current process and understanding using Minitab: Part 1: I already have my data ...
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0answers
964 views

Adjust p-values for variance inflation factors

I'm fitting linear mixed models and I have slightly inflated p-values due to multicollinearity. I deleted the factors with the highest VIFs until none of them was larger than 3. The VIFs tell me, ...