# Tagged Questions

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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### 0-centering a kernel matrix: which formula is the correct one?

I'm trying to implement the algorithm in this paper. As you can see at page 4, it is explained how to 0-centering a pxp symmetric Kernel matrix ...
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### R: Quadratic Regression with interaction: when to center?

I have a statistical question. I have data from an experiment with two conditions (dichotomous IV: 'condition'). I also want to make use of another IV which is metric ('hh'). My DV is also metric ('...
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### How is the first column of the matrix orthogonal to all the others

 \mathbf{X}_{n\times(r+1)} = \begin{bmatrix} 1 & (x_{11}-\bar x_1) &\cdots & (x_{1r}-\bar x_r) \\ 1 &(x_{21}-\bar x_1) &\cdots & (x_{2r}-\bar x_r) \\ ...
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### Group mean centering predictors for crossed random effects

I'm fitting a mixed-effects model, in which I wish to test the effect of $X$ on $Y$, with crossed random intercepts and slopes for each subjects $S%$, and for each level of an additional grouping ...
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### Zero-centering the testing set after PCA on the training set

I have a training set of data on which I do principal components analysis (PCA) and save the loadings/eigenvectors/coefficient matrix. I want to use the eigenvectors to transform my testing data into ...
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### Does centering or mean normalizaiton alone every help in feature scaling?

In feature scaling, one way is to subtract the mean (centering) and then divide by the standard deviation for all data points. Suppose we just centered the data and didn't divide by the standard ...
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### Should I center time variant predictors in repeated measures multilevel models?

I have a multilevel model built coinsidering repeated measures on students. Students performance may vary depending on study hours and tutoring hours before each exam. Should I center the predictors ...
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### Imputation of missing data before or after centering and scaling?

I want to impute missing values of a dataset for machine learning (knn imputation). Is it better to scale and center the data before the imputation or afterwards? Since the scaling and centering ...
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### The order of Data Centering and Data Transformation

Edit: I just read a related post (How to include $x$ and $x^2$ into regression, and whether to center them?) which mentions that centering a variable creates a new variable. However, as the comments ...
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### Between-subjects effect becomes non-signicant after centering covariate. Should I center or not?

I've used a general linear model function to run an ANCOVA, involving a categorical predictor (with two levels), a continuous predictor, and their interaction effect. If I don't center the ...
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### When should one centre variables in a cox proportional hazard model and when not? [duplicate]

I want to use a Cox proportional hazard model in order to analyze the prognostic value of a certain variable (I divided it in quartiles and so I have 4 categories) with respect to the time to event (...
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### Is scaling data valid for Kruskal-Wallis test?

I have a dataset of fresh matter (FM) weights of salad measured in field over time (6 Dates, 40 Plants each). Those are measured independently, so at every date different plants were measured. As in ...
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### Which mean to use for centering variables when sample definition varies

I am centering variables that enter interaction terms in my linear regression. To check the robustness of my results, I exclude certain cases from the original sample, and re-run the regression ...
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### How to include $x$ and $x^2$ into regression, and whether to center them?

I want to include the term $x$ and its square $x^2$ (predictor variables) into a regression because I assume that low values of $x$ have a positive effect on the dependent variable and high values ...
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### Do you ever center AND standardize variables in multiple regression?

Do you ever center AND standardize variables in multiple regression? It seems as if standardization would automatically center variables...is this true?
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### Is centering a valid solution for multicollinearity?

Let's assume that $y = a + a_1x_1 + a_2x_2 + a_3x_3 + e$ where $x_1$ and $x_2$ both are indexes both range from $0-10$ where $0$ is the minimum and $10$ is the maximum. I found by applying VIF, CI and ...