# Questions tagged [cooks-distance]

A measure of the influence of a single observation in regression modelling.

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15 views

### Cook's distance and AUC/Accuracy

I am working with balanced data set and trying to build a logistic regression model for prediction. I have 322 observations, 6 continuous independent variables, 152(170) positive(negative) values. ...
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### The algebraic equivalence of two expressions for Cook's distance

I have read several times across difference sources now that the definition of Cook's Distance, which is $$D_i=\frac{\sum_{j=1}^n(\hat{y}_j-\hat{y}_{j(i)})^2}{ps^2}$$ (where $\hat{y}_j$ is the jth ...
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### Cooks Distance for multiple observations

I would like to determine the combined influence of a group of observations on a linear regression model, but I am not entirely sure how to compute the Cook's Distance for that. I know that for a ...
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### Finding the Case with the Highest Influence

I'm new to regression and diagnostics so if this seems a bit basic/unnecessarily long-winded that's why. I perform a multiple regression of a response variable on four predictor variables. There are ...
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### What is the logic behind Cook's distance cutoffs?

I would like to better understand the logic behind different cook's cutoffs, so I can come up with a reasonable cutoff to use for diagnosing influential points in my data. Wikipedia explains the ...
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### Does it make sense to compare Cooks distance between two models

If I have a greater amount of observations that high values of Cooks distances in one model than another does that suggest that the model is not as suitable? For example, here ...
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### Cook's distance - problem with understanding

I have a problem with calculating Cook Distance (I'm trying to understand it). Ok so here is the task and my 'solution'. I'm asking for comment, is it ok, or what do I wrong. We have simple linear ...
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### Cooks distance and categorical features

I try to detect outliers by cook´s distance for a regression. If I only use numeric features as explanatory variables it works fine. However, if I add categorical features to the explanatory features ...
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Sample data ...
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### Sensitivity Measures for GEE Model

Is there any method (e.g. like Cooks D) implemented in R to identify leverage points for GEE Models? I used geepack to fit my models and would like to do a sensitivity analysis now. However, I don't ...
309 views

### Cooks Distance Confusion

I know there are a lot of questions along this vein, but none seem applicable to the data I have. Essentially I have run a one-way ANOVA using a variable composed of 4 different groups (A:D) and the ...
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### How to find an optimal combination of predictors in predicting outcome?

It is a marketing project in which I need to compare the effectiveness of six different marketing tools in terms of sales. the tools are like "No. of times a salesman personally visit to the customer",...
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### Cook's distance vs. hat values

What exactly does Cook's distance measure? And how is this different from what hat values measure? I know hat values measure how distant a point it form its corresponding fitted point. I also know ...
1k views

### A better Outlier Detection approach! [duplicate]

Currently I am using Cook's distance to detect outliers in multivariate data. Is there any better approach than Cook's distance for the same?
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### Can I use Cook's distance to detect outliers without a Dependent Variable?

I asked a previous question that I think was not worded well and long so I'm trying again! I have 3 different tasks and performance for 20 levels in each task, therefore, performance for 60 levels in ...
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### Should I remove the influential points in this case?

I build a linear model from a small dataset with ...
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### Plotting Cook's Distance Lines [closed]

I've currently created a plot using Python showing leverage vs residuals of some data. I want to plot Cook's Distance lines like shown in Case 2. How would I go ahead with this?
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### Understanding Cook's Distance

I'm trying to use Cook's Distance in order to detect outliers in high-dimensional datasets. However, I've found some troubles in order to do such thing. Usually, once I've built the linear model and ...
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### Outliers in Linear Regression that ONLY revert significance

When doing linear regression, all sorts of influence checks (Cook's Distance, leverage, dffits, dfbetas, covratio) can be conducted on the data points. Each of these are literature-supplied with some ...
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### How to calculate Cook's distance for lm.ridge objects in R

How can I calculate Cook's distance for lm.ridge objects? I first created a glmnet object and carried out ridge regression ...
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### Justification for Dummy Variable When Cook's < 1

For a class project, I have a data set of restaurants and health inspection scores. I want to indicate if a restaurant was closed or not due to violations as this seems to be a significant predictor ...
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### Casewise diagnostics and testing assumptions for a mixed effect logistic regression in R

I am modelling a binary outcome (Buried), that has two predictors: Offset (a 3 level factor) and width (continuous predictor). In addition, multiple data points came from the same unit -- a chamber, ...
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### What to do with an outlier that once removed prevent model convergence?

So, I'm performing generalized linear mixed models with a poisson distribution and an offset. When looking at the Cook's distance, I found gigantic values (above 3000). When removing the concerned ...
185 views

### Can Cook's distance plot only be used for least squares regression?

If Cook's distance can only be used for least squares regression, what are some alternatives that will give me a similar plot for a Gamma model or any regression model from the exponential family?
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### How do I remove outliers in dataset?

I have a data-set (185 rows) with 20 predictors and 1 dependent variable. I have applied Cook's distance and then 4/N formula to remove some of the outliers in 1st iteration. Should I do this ...
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### Do points with high Cook's distance necessarily have a high standardized residual, and vice-versa?

I have two questions below: Could a data point be an influential point if its cook distance is outstanding(greater than 4/(n-p-1)) while its standardised residual is less than 2? It looks like to me ,...
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### Diagnostics for generalized additive model vs linear model

I am doing an analysis in R and I have the model: lm(birthrate~education+employment+lo(latitude, longitude),data=data2). It seems to be a generalized additive ...
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### Influential case - to remove or not to remove?

I'm doing a multiple regression analysis with 3 predictor variables (RELAT, SSS and FAITH), and the criterion variable is SSE. I have found that SSS is a mediator between RELAT and SSE, and FAITH is a ...
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### Cook's distance in detecting outliers

According to my understanding, Cook's distance measures the influence of each observation by excluding points when fitting a model. So I assume it could be an reasonable approach for outlier detection?...
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### Inference of Cook's Distance Plot

What can we infer from cook's distance or the cook's distance plot of regression model? How can it be used to refine model further ? Should we remove the values which are high influencers or lie ...
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### Multiple Regression Assumptions

This may seem like a basic question, but I'm verifying the assumptions for a multiple regression and have some trouble wrapping my head around homoscedasticity. I have a few questions listed below: 1)...
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### Outlier detection in multivariate data

I have a table with thirty variables and am interested in finding the outliers (rows). Assuming that my variables are independent I am hesitant whether I should use Cook's distance as it requires to ...
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### Is there a bound of percentage/number of influential points for a given size sample?

Consider for a given data set of size $N$, and we do a linear regression analysis on it. We know that we can define influential points among this dataset by setting a threshold value on the Cook's ...
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### Interpreting linearity in regression when there are outliers

I am trying to determine whether this regression meets all of the assumptions one needs to adhere to when carrying out a multiple linear regression. In looking at the residual plots below, it seems to ...
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### Removing outliers based on cook's distance in R Language

I have this R code for linear regression: fit <- lm(target ~ age+sales+income, data = new) How to identify influential observations based upon cook's distance ...
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### Is it possible to derive Leverage figures without a Hat Matrix?

I ran into an impasse while attempting to write code for Cook's Distance: when a regression model reaches only a moderate size, I can't derive a Hat Matrix through my normal matrix math routines ...
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### How to distinguish suspicious leverages?

Given a linear model and the following hatvalues and influence.measures, how can I say which measurements are suspicious? I mean ...
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### Elastic net: dealing with wide data with outliers

Recently I was working on a dataset with ~300 observations and 1500 predictors. I used the glmnet package in R to fit an elastic net model, which gave me a cross-...
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### Interpreting case influence statistics (leverage, studentized residuals, and Cook's distance)

I just wanted to clarify some things about leverage, studentized residuals, and Cook's distance: Does a large (in absolute value) studentized residual mean that a case is an outlier? Does a large ...
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### Model selection

I have a small dataset of 37 observations with students' performance on both cognitive tests (5) and professional tests (6). My goal is to predict professional tests (DV) with cognitive tests(IV). To ...
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### Selecting a multiple linear regression model with categorical variables

I am trying to analyze the Berkeley Guidance Study to practice multiple regression models, which has 10 continuous variables, 1 categorical variable (with two categories) and the response variable. ...
247 views

### How can a regression be significant yet both predictors be non-significant? [duplicate]

I know this question has been asked in a slightly different form here. But my question differs and because of the forum rules I can't post on that thread. I have 2 independent variables, n=32, highly ...
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### Generalized Linear Mixed Models: Diagnostics

I have a random intercept logistic regression (due to repeated measurements) and I would like to do some diagnostics, specifically concerning outliers and influential observations. I looked at ...
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### Checking for outliers in a glmer (lme4 package) with 3 random factors

I have a question relating to the checking for outliers and / or influential points in my dataset using a glmer model with 3 random variables. I'm investigating the ...