Questions tagged [cooks-distance]

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

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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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582 views

Identifying outliers in the data

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 ...
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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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6k views

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 ...
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905 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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213 views

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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1answer
812 views

Should I remove the influential points in this case?

I build a linear model from a small dataset with ...
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1answer
3k views

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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5k views

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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1answer
139 views

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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309 views

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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63 views

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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1answer
805 views

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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2answers
146 views

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 ...
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1answer
165 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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486 views

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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1answer
452 views

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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1answer
489 views

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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1answer
98 views

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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887 views

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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504 views

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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693 views

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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1answer
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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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291 views

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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151 views

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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1answer
966 views

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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1answer
1k views

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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133 views

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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878 views

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. ...
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1answer
246 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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1answer
546 views

Cook's Distance

The formula of Cook's distance is $$D_i=\frac{(\hat Y-\hat Y(i))^{\prime}(\hat Y-\hat Y(i))}{p\times MSE}$$ where, $\hat Y$ is the prediction from the full regression model and $\hat Y$ is a $(n\...
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396 views

What is the $p$ in Cook's distance?

In the equation for Cook's distance: $$D_i = \frac{\sum_{j=1}^{n}(\hat{y}_j - \hat{y}_{j(i)})^2}{p MSE}$$ the value of $p$ is defined as "the number of fitted parameters in the model." What does ...
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1answer
16k views

Cook's distance cut-off value

I have been reading on cook's distance to identify outliers which have high influence on my regression. In Cook's original study he says that a cut-off rate of 1 should be comparable to identify ...
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1answer
742 views

Cook's distance and $R^2$

I am currently running a linear regression and calculating its $R^2$ After that. I calculate the Cook's distance of all points and throw away from the analysis all of the points with a distance ...
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2answers
2k views

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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1answer
2k views

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 ...
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1answer
254 views

What is the explanation for a regressor losing statistical significance when a high leverage point is dropped?

I'm currently working on an Econometrics project and I've come to a point where I've dropped a high leverage point as identified by cook's distance and a leverage plot (had observations that were ...
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3answers
6k views

Residuals for logistic regression and Cook's distance

Are there any particular assumptions regarding the errors for logistic regression such as the constant variance of the error terms and the normality of the residuals? Also typically when you have ...
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How to read Cook's distance plots?

Does anyone know how to work out whether points 7, 16 and 29 are influential points or not? I read somewhere that because Cook's distance is lower than 1, they are not. Am, I right?
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1answer
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What kind of residuals and Cook's distance are used for GLM?

Does anybody know what the formula for Cook's distance is? The original Cook's distance formula uses studentized residuals, but why is R using std. Pearson residuals when computing the Cook's distance ...
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1answer
5k views

How to get Cook's distance and carry out residual analysis for non-lm() and non-glm() models in R?

I usually use the plot(lm()) or plot(glm()) (combined with par(mfrow=c(2,2)) to analyze ...
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7answers
6k views

Correcting for outliers in a running average

We have a daemon that reads in data from some sensors, and among the things it calculates (besides simply just reporting the state) is the average time it takes for the sensors to change from one ...