# Questions tagged [centering]

Centering involves subtracting the overall sample mean score from the original score; standardizing does the same followed by dividing by the overall sample standard deviation.

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### Whats the motivation to demean variables when estimating an interaction effect? [duplicate]

I am trying to estimate a regression model where I am interested in the effect of a certain magnitude, probability and expected value (probability * magnitude ) on reaction times. I was told that it ...
30 views

### Mean-centering variables in glmer

I have the following model in r that compares the differences between dives where whales fed and dives where whales didn't fed (distribution is binomial: presence of feeding (foraging) = 1, abscence = ...
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### Why does centering NOT cure multicollinearity?

In several posts, such as Is centering a valid solution for multicollinearity?, it states that centering doesn't solve multicollinearity because "it's a linear transformation." I just made ...
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### Why Ridge regression doesn't depend on centering $y$ in sklearn?

In sklearn's manual for Ridge they wrote the following about its parameter "fit_intercept": But it seems that Ridge model doesn't depend on whether $y$ is centered or not: ...
13 views

### Scaling/Transforming Data which is already [0,1]

I have some data with a lot of Variables (Measures) which are already [0,1]. But each variable is differently distributed. So some look like they are exponential distributed, some are quite normal ...
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### Applying de-standardised ridge regression coefficients to new test data - how to best handle the mean of y_test?

this is my first post on Stackexchange, so please correct me in any way if I am doing it wrongly. I just stumbled across this question, I was battling with the same issue, but the posts there ...
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### Is it possible to back-transform predictions from KNN regression with 2 centered and scaled predictors?

My question is: Is it possible to back-transform predictions from a KNN regression model built from 2 centered and scaled predictors? I would like to make predictions on a new dataset using a KNN ...
10 views

### Interpreting repeated-measures oneway ANCOVA

I have a question on how to run a repeated-measures oneway ANCOVA. I have only one within-subjects factor (time) and I am interested in how a construct changes from T1 to T2. I would also like to add ...
22 views

### Should we center a Season Variable for regression?

Suppose that we have the following model $Y = b_{0}+b_{1}*Season +b_{2}*Income$ In order for $b_{0}$ to refer to the expected value of $Y$, we should center the variables Season and Income. However,...
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### Do I use the mean vector from my training set to center my testing set when dimension reducing for classification?

Please let me know if this is the right place to ask this (or if any of my tags are wrong) or if I need to write this any differently. Do I use the mean vector from my training set to center my ...
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### How to center level-2 variables in unbalanced two-level models?

Let's say I have a sample of 200 students and they are clustered in 10 different classrooms. However, the sample is unbalanced such that some schools have more than 20 students and others have fewer ...
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### How can centering predictor variables reduce correlation between them?

In Statistical Rethinking by Richard McElreath on pg. 320 he states “centering predictors can aid in inference, by reducing correlations among parameters”. For a linear equation with an interaction ...
398 views

### categorical predictors in partial least squares

I am interested in running a partial least squares analysis using PROC PLS in SAS 9.4. I understand that, by default, the predictors and response variables in PLS are centered to a mean 0 and scaled ...
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### Mean centering and normalization along every dimension or over whole dataset

I'm working a side project which involves using a pre-trained CNN and I came across a piece of code that made me question some of my recently gained knowledge around mean centering and normalization. ...
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### centering in mixed effect logistic regression

I am working with a mixed-effect logistic regression with two independents (a and b, dummy coded 0 or 1), which have a fixed effect for a, b and the paired interaction as well as a random effect of M ...
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### Is it wrong to standardise a variable and then centre it for use in multiple regression? [duplicate]

Is it wrong to standardise a variable (e.g. polygenic risk score) and then centre it for use in multiple regression?
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### Why are the normal equations $X_c(X_c'X_c)^{-1}X_c^Ty$ for centered OLS?

I'm working through a centered OLS problem. If $X$ has an intercept column, $y = X\beta + \epsilon \Rightarrow y = X_c\beta_c + \gamma_0 + \epsilon$ where $X_c$ is the centered design matrix. My ...
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### Multicollinearity and centering [duplicate]

I read nearly all topics about collinearity but still have some questions... I know: multicollinearity is a problem because if two predictors measure approximately the same it is nearly impossible to ...
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### Multinomial logistic regression - centering and using dummy coding?

I have two IV's: cognitive ability test scores (a continuous variable), and task difficulty levels (3 levels: easy, medium, difficult) I want to predict a categorical outcome with 3 types of behavior (...
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### Rank of N x D vs D x N matrices

If $X$ is a random $N \times D$ matrix where $N > D$, then why is the rank of X - mean(X, 1) $D$ while the rank of ...
104 views

### choice of mean for mean centering

I am doing statistical analysis of empirical data using a a generalized ordered regression model. I would like to test for interaction terms. I have a 3-level categorical IV (coded as 2 dummy ...
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### Analyses when IVs highly correlated - is there anything I can do?

I'm doing some analyses in which I have 1 continuous independent variable (IV) and 1 dichotomous independent variable (IV2) that's a demographic covariate. I'm now realizing that they are extremely ...
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### Why does my centered variable not have zero mean?

It is well established that centering a variable, i.e. subtracting the mean of that variable from every value produces a variable with zero mean. For example: ...
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### Center data in quantile regression?

I have 25 years of nest initiation dates, I used quantile regression to look for changes in the distribution over time, as well as to look in detail to early and late breeders. My model would be ...
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### Should I use mean centering or not?

I am using a logistic regression model. I want to see interaction effect of a continuous Independent variable on the relationship of another binary independent variable and the dependent variable(DV ...
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### How to represent multiple data by single value

I have three inputs x1,x2,x3 and to each single input there are three outputs y1, y2, y3. (1) x1 --y1, y2, y3 (2) x2 --y1, y2, y3 (3) x3 --y1, y2, y3 The Whole whole set has to be represented by ...
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### Representative terms per clusters based on tf-idf

I have a result of text clustering based on TF-IDF. I have $k$ clusters. How can I get the representative terms for each cluster $I=1,\dots,k$ using the TF-IDF matrix? Is there any standard way to do ...
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### Decision to center fixed effects in GLMMs in lme4

I'm constructing a GLMM using lme4 in R, and am unsure as to when it is and isn't best practice to center fixed effects. For this model (with logit link), for example: ...
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### Should I center the data when performing Laplacian Eigenmap or any other manifold learning?

Suppose I have a high dimensional non-stationary non-linear time series, then is it advisable to center the data on the mean when performing laplacian eigenmap? I've heard somewhere that when ...