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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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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2answers
308 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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0answers
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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1answer
161 views

Variance Inflation Factor and Condition Indeces

My data is cross-sectional macroeconomics data. I have six independent variables (x1,x2,x3,x4,x5,x6) plus 2 dummies (d1,d2) plus 2 interactions terms (d1*x1,d2*x1).I am testing my data for ...
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0answers
432 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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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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0answers
175 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
46 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 ...
2
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0answers
82 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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0answers
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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0answers
238 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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0answers
155 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
299 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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0answers
58 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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0answers
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
281 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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0answers
422 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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0answers
758 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
283 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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0answers
4 views

In what form should my features be in when running a model trained on features transformed through Weights of Evidence?

I have trained an anomaly detection model on features transformed/selected by means of the Weights of Evidence and Variance Inflation Factor approaches. My question is how should I go about running ...
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0answers
206 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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1answer
61 views

How can I use linear/logistic regression for inference with colinear variables and a smallish dataset?

I have a dataset of around 120 observations, with 30 calculated variables and I am trying to predict a continuous response (result of an experiment) using those 30 variables. Ideally the smallest ...
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0answers
73 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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0answers
34 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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0answers
210 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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0answers
80 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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0answers
90 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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0answers
119 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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0answers
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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1answer
1k views

Why is Variance Inflation Factors(VIF) in Gretl and Statmodels different?

I have 3 variables R&D Spend, Administration and Marketing spends. I wanted to calculate VIF and eliminate a variable for better fit to the model. I tried to use the solution at ...
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0answers
278 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
262 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
185 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
339 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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1answer
170 views

Exploratory data analysis. What features are important?

I am trying to fit the number of crimes in a city with some enviromental variables (aka my features). I'm using a Poisson/Negative Binomial model since I have count data. The problems are: selecting ...
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2answers
287 views

Multicolinearity Test for Multiple Multivariate Regression

I have multiple independent variables and multiple dependent variables, some categorical and some quantitative. I have created a data sheet with dummy columns appropriate to each categorical variable. ...
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0answers
357 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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0answers
263 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
228 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
19 views

How to show that VIF's are the main diagonal elements of $\mathbf{T\Lambda^{-1}T'}$?

I'm stucked in the Exercise 9.29 of Introduction to Linear Regression Analysis (5th edition), by Montgomery: 9.29) Show that if $\mathbf{X'X}$ is in correlation form, $\mathbf{\Lambda}$ is the ...
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0answers
13 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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1answer
34 views

How is GVIF calculated for categorical variables?Also is there any other way to detect multi co-linearity of categorical variables?

I was tring to find a way to remove the redundant categorical variables as features. I believe GVIF would give high value for the redundant/multicollinear categorical variables. Please let me know if ...
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0answers
69 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
22 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 ...
0
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1answer
46 views

Excellent model fit but high VIF

I want to use a predictive model for a time series variable M that is related to an other variable X. I can generate independent scenarios for X and I need to generate corresponding values for M. ...
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0answers
243 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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0answers
104 views

Variance inflation factors for time series

R code: I got an error by using vif function. ...
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0answers
488 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 $R_j^2$ ...