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.

Filter by
Sorted by
Tagged with
1
vote
0answers
11 views

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 ...
4
votes
1answer
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 = ...
1
vote
0answers
31 views

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 ...
0
votes
0answers
18 views

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: ...
0
votes
0answers
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 ...
0
votes
1answer
27 views

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 ...
0
votes
0answers
10 views

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 ...
1
vote
0answers
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 ...
0
votes
1answer
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,...
0
votes
2answers
35 views

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 ...
0
votes
1answer
15 views

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 ...
5
votes
2answers
267 views

p-values change after mean centering with interaction terms. How to test for significance?

I assumed the following interaction model: $$y = \beta_0 + \beta_1 x_1 + \beta_2 x_2 + \beta_3 x_3 + \beta_4 x_2 x_3$$ And then applied mean centering: $$y = \beta_0 + \beta_1(x_1 - \bar{x_1}) + \...
0
votes
0answers
241 views

Mean-centering changes the values of regression coefficients with interaction terms [duplicate]

To my knowledge, mean-centering does affect the values of regression coefficient for variables involved with interaction terms. But it does reduce the standard errors of the coefficient estimates for ...
1
vote
0answers
52 views

How does centering affects the interpretation of the marginal effects?

I am trying to understand how centering continuous variables in a linear regression that includes an interaction term between two continuous variables, affect the interpretation of marginal effects. ...
0
votes
1answer
83 views

Within-subject centering of a repeatedly measured dichotomous variable in a multilevel model?

I'm currently working on a nested data set consisting of 100 subjects which answered several questions at home on five consecutive days (ecological momentary assessment). Among them, they were asked ...
0
votes
0answers
34 views

To center or not to center? [duplicate]

I am using a linear regression model to determine the effect of diet score at baseline as predictor of weight at follow up where: lm(weight_followup ~ Diet_Score*weight_base) When I center my ...
-1
votes
1answer
35 views

Should grand-mean centering happen in long or wide dataset?

This seems like a simple question but I've been having a hard time finding an answer. In a long daily diary dataset where each day has a row, the person mean for a given level-1 variable is repeated ...
1
vote
0answers
23 views

Disaggregating between/within person variance for categorical level 1 variables?

I'm working with daily diary data that include a categorical variable indicating which of 4 possible events happened that day. I dummy-coded this variable and entered it into my multilevel model. ...
0
votes
0answers
154 views

Mediation and centering

I am running a mediation model with 2 interaction terms (gender x happiness and gender x hours spent working per week) and one dependent term (income). I am wondering if I should mean center these ...
4
votes
1answer
875 views

Mean centering interaction terms

I want to mean center my interaction terms in a regression model (i.e., make the mean zero for each variable). I understand that I am supposed to mean center my variables first and then multiply them ...
0
votes
0answers
40 views

Centering variables in multidimensional data

Assume you have a panel data set, that means for each car (CAR), with several individuals (IDs), the dependent variable is given as the power (POWER) created by an engine, over time (time). Further ...
1
vote
1answer
169 views

In linear regression, what would it do to center the label?

In this question linked below, it was addressed why we would center the features in linear regression. When conducting multiple regression, when should you center your predictor variables & when ...
1
vote
1answer
62 views

Need to center continuous variables in GAMs?

This is just a quick question, but I remember reading somewhere that continuous variables used in splines for generalized additive models ought to be centered (especially for GAMs rather than just as ...
2
votes
1answer
45 views

Centering input data for Robust PCA (RPCA)?

I know that before running Principal component analys, the input data needs to be centered around its mean (subtract the mean from each keypoint) before running the algorithm. Do I need to center my ...
1
vote
0answers
30 views

Does centering really help interpret the intercept? [duplicate]

Various people have advocated centering independent variables in regression, on the grounds that the intercept then refers to a sensible point (the mean of each IV) rather than the often impossible ...
1
vote
0answers
77 views

Within-person centering the outcome variable?

What do you think of within-person centering the outcome variable? If my research questions is clearly about within-person effects (in a longitudinal multilevel model), can I just use the centered ...
4
votes
1answer
174 views

Centering in longitudinal linear mixed modeling - center by participant mean, timepoint mean, or participant by time grand mean?

EDIT: I was incorrectly looking to center my outcome variables. Only center predictors, and decide on group mean or grand mean centering by how you want to interpret your intercept. I have 150 ...
1
vote
1answer
156 views

Grand-mean centering in GLMM changes estimates for variance (and everything else)?

I know that when running a linear mixed effects model, centering around the grand mean should change the estimates for the coefficients, but not the estimate for the variance. For example, I have ...
2
votes
1answer
53 views

symbol for mean centering

I am struggling to write up an equation in the manuscript of a scientific paper, where two of the terms are mean centered around the group mean. In addition, the mean centering is done with excluding ...
0
votes
1answer
463 views

Penalize the intercept in lasso (L1) penalized logistic regression or not?

In logistic regression: $log(\frac{p(x)}{1-p(x)}) = \beta_0 + \beta_1x$, let $x' = \frac{x-\bar{x}}{\sigma_x}$, then in terms of the centered and scaled varaible $x'$ , $$ log(\frac{p(x')}{1-p(x')}) ...
3
votes
1answer
262 views

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 ...
0
votes
1answer
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 ...
1
vote
0answers
75 views

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. ...
1
vote
1answer
140 views

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 ...
0
votes
0answers
26 views

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?
0
votes
1answer
123 views

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 ...
1
vote
0answers
996 views

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 ...
0
votes
0answers
170 views

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 (...
1
vote
1answer
28 views

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 ...
1
vote
2answers
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 ...
3
votes
2answers
112 views

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 ...
3
votes
1answer
2k views

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: ...
1
vote
0answers
61 views

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 ...
0
votes
1answer
637 views

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 ...
-1
votes
1answer
27 views

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 ...
2
votes
0answers
177 views

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 ...
0
votes
1answer
1k views

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: ...
1
vote
1answer
51 views

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 ...
1
vote
0answers
46 views

Why does the standard error of the intercept change when we shift the axis, say by centering? [duplicate]

I was trying to understand how the calculations are done behind lm() function in R using mtcars dataset. I understand that ...
1
vote
0answers
56 views

Variable centering on the sampling distribution of the coefficient estimates

I think the question may be silly but I'm trying to learn statistics and R and this is really hard for me because I'm a newbie of both. I have this exercise to do. Carry out a simulation ...