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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24 views

Pre-processing (center + scale, box-cox transformation) inside cross-validation?

I have extracted features and I have now a matrix where the rows are the data points and the columns are the features. Of course, I have to center and scale (zero mean and unit variance) each feature ...
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1answer
79 views

How does centering make a difference in PCA (for SVD and eigen decomposition)?

What difference does centering (or de-meaning) your data make for PCA? I've heard that it makes the maths easier or that it prevents the first PC from being dominated by the variables' means, but I ...
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17 views

Centering in the presence of interactions with categorical predictors?

I understand that always scaling covariates prior to regression analysis is controversial advice. See for example Andrew Gelman's blogpost and comments, or many crossvalidated questions such as this ...
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1answer
36 views

Centering variables in regression leads to the same model of original variables, why still doing that?

The regression model y= b0+ b1 x + b2 x^2 + b3 x^3 and the second regression model y = b0 +b1 (x-u) + b2 (x-u)^2 + b3 (x-u)^3 where u is the mean of x These two models lead to the same curves, or ...
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16 views

Should I use mean-centering on predictors for collinearity involving the intercept?

In one of my linear regression models, a predictor showed collinearity with the intercept based on condition indexes and variance decomposition proportions diagnosis. Then I found that this predictor ...
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40 views

Motivation to center continuous predictor in multiple regression for sake of multicollinearity?

I'd like to discuss the centering of continuous predictor variables in multiple linear regression with an interaction term for the sake of "relieving" multicollinearity. I've read about ...
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41 views

Centering for the regression. How to do it properly?

I have read a paper described an analysis of using support vector regression. In the paper it mentioned: It is worth mentioning that, in our implementation, we subtract the mean value of the ...
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1answer
107 views

Regression: centered vs. uncentered predictors [duplicate]

I'm trying to understand how/why centering predictors in a 2 predictor regression model would change the coefficients Lets say I have 2 centered predictors and an interaction term, predicting a ...
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59 views

Mean and residual centering, orthogonal polynomials and effect coding

I understand that in order to be able to interpret main effects / lower order terms in a more intuitive way in linear regression models with interaction effects one should either use mean or residual ...
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62 views

centering constraints on ti() terms in MGCV

I have some raw data on which I compute percent changes, and I calculate rolling averages of two different lengths on the percent changes. I want to use a tensor interaction of the two rolling ...
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1answer
145 views

centering and scaling dummy variables

I have a data set that contains both categorical variables and continuous variables. I was advised to transform the categorical variables as binary variables for each level (ie, A_level1:{0,1}, ...
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68 views

LDA scores too big

I'm trying to do dimensionality reduction with linear discriminant analysis (LDA) in MATLAB. I'm using this code to calculate the coefficients. But I'm confused whether (and when) should I center the ...
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70 views

Principal Component of non-centered data and PCA-Transformation

I am reading a chapter about principal component analysis (PCA). It states that for any random varible $X \in \mathbb{R}^p$ with $n$ observations, $E[X] = \mu$ and $Cov[X] = \Sigma$ the i-th PC is ...
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1answer
23 views

Clarification on Prediction with a Regression Model using Centered Variables

As I understand it, for a regression model, centering the variables around their means can be helpful since it makes the intercept term the expected value of $Y_i$ when the predictor variables are set ...
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98 views

Centering variables in R [closed]

Do centered variables have to stay in matrix form when using them in a regression equation? I have centered a few variables using the scale function with ...
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474 views

Standardized VS centered variables

I have found many useful posts about standardized independent variables and centered independent variables on stats.exchange.com, but I am still a bit confused. I am asking you an evaluation of what ...
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101 views

How do statistics packages (e.g., fitglm in MATLAB, SPSS/SAS/Stata) handle mean centering for higher order terms? [closed]

Many questions (e.g., Centering in linear regression & How to include a linear and quadratic term when also including interaction with those variables? ) have been asked about mean centering (aka ...
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3answers
265 views

Mean centering - before regression or observations that enter regression?

I am using Stata 13 to estimate a simple model with interaction terms. To give the coefficients a meaningful interpretation at zero, and to avoid multicollinearity, I am mean centering variables. I ...
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35 views

Multicollinearity Diagnostics of Mean-Centered Interaction Terms

Interaction terms in moderated regressions exhibit high multicollinearity due to the high correlations with their main effects in case of uncentered data; for Normal distributed variables this is not ...
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40 views

Is there moderator or not? Centering and unsignificant b

I am trying to check if the relationship between X and Y is a moderated by M. Here is my model: Y = b0 + b1*X + b2*M + b3*X^2 + b4*X*M + b5*X^2*M where X - independable variable, M - moderator, Y - ...
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1answer
157 views

How should I implement this interaction between a continuous and categorical predictor?

I have a continuous outcome variable. I understand that if I have a binary predictor, and a continuous predictor, and an interaction, then the model looks like this: $y_{i} = \beta_{0} + ...
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69 views

Standardization/Centering of Longitudinally-measured variable

Could someone possibly help me with the following issues that I am mentally stuck at? Thanks so much! I have 200 variables M1, M2, .... Mx. Each is measured at three time points 0, 30, 120 min. The ...
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1answer
69 views

Centering in linear regression

I am trying to fit a quadratic to my model, I have tuples (x,y). The choices are, 1) lm(y~x+I(x^2)) 2) ...
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173 views

How does one interpret a demeaned log interaction term?

I am having problems interpreting my regression equation. I want to know the effect of an increase in variable $x$ on $y$ for different values of $z$, but as it's in logs and the interaction term is ...
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1answer
98 views

Can $x'x$ be written as correlation matrix?

$x'x=$ $$ \begin{bmatrix} \sum_{i=1}^{n}(X_{1i}-\bar X_1)^2&\sum_{i=1}^{n}(X_{1i}-\bar X_1)(X_{2i}-\bar X_1)\cdots & \sum_{i=1}^{n}(X_{1i}-\bar X_1)(X_{ki}-\bar X_k) \\ ...
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2answers
203 views

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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102 views

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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1answer
275 views

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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51 views

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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1answer
80 views

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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1answer
139 views

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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2answers
715 views

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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2answers
258 views

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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16 views

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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34 views

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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1answer
49 views

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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3answers
342 views

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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1answer
192 views

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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3answers
2k views

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 ...
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0answers
42 views

Centering variables before running PCA [duplicate]

I am learning about PCA, regarding PCA I need to know that given a dataset is it always necessary to use centering? what if I don't center the variables used in PCA?
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0answers
931 views

How does knnimpute of the preprocess function work?

I am new to R and I use a script I do not completely understand. It preprocesses a dataset for data mining. At one point, the data (stored in fil) should be ...
2
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1answer
2k views

Centering data in multiple regression

In a multiple regression analysis (with 4 continuous predictors and 2 categorical factors), we mean centered the data (for each continuous variable) due to issues of multicollinearity when the ...
2
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0answers
235 views

Which variables should I transform, center, and/or standardize in my data for Principal Component Analysis?

I have multiple datasets that I am attempting to use principal component analysis (PCA) on in order to infer the underlying structure of the data. I'm attempting to predict growth increment of ...
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2answers
62 views

Does it make sense to partially scale the data matrix X in regression?

For some reason my supervisor wants me to centre only the independent variables that are used in interaction terms. I have never heard of such a practice. Does it make sense to partially centre data ...
3
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1answer
2k views

Converting standardized betas back to original variables

I realise this is probably a very simple question but after searching I can't find the answer I am looking for. I have a problem where I need to standardize the variables run the (ridge regression) ...
3
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0answers
95 views

Should I de-mean a predictor variable before a dummy interaction

Suppose I have the following time-series linear model where $\beta$ is misspecified: $Y(t+1) = \alpha + \beta X(t) + \sum_{i=1}^{10000}\gamma_i Z_i(T) + \varepsilon$ where all parameters are in ...
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2answers
1k views

How to include a linear and quadratic term when also including interaction with those variables?

When adding a numeric predictor with categorical predictors and their interactions, it is usually considered necessary to center the variables at 0 beforehand. The reasoning is that the main effects ...
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2answers
162 views

Centering when using splines in R

I am having trouble understanding why centering seems to only work with simple linear models and not with splines for example. I am using centering to report the estimated group differences at ...
2
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0answers
179 views

Interaction Term Insignificant but Composite Variable Significant

I have 4 latent variables each with 3-7 indicators. I created a composite for each variable by summing the data and then mean-centering (variables have some collinearity issues, highly related). ...
4
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181 views

How to do centering if I have a quadratic term?

I have been trying to run a multilevel model with both a linear and a quadratic term for income as my main variables of interest. It looks something like: \begin{eqnarray} ...