Shifting and rescaling data to assure zero mean and unit variance.

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15 views

Do I standardize the response value as well? [duplicate]

In linear regression when my variables have a different scale do I have to standardise only the independent variables or the response as well?
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3answers
207 views

Can I test for correlation between variables before standardize them?

What I want to do is to construct GLMM's to evaluate resource selection, and I have a set of variables (some representing distances and others representing % of land cover). Can I test for ...
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11 views

Question regarding variables transformation for GLMM's

I have a response variable (binary:1/0) and a set of explanatory variables, with different units: some have values in %, others in meters (distances, altitude and differences between elevation pixels),...
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10 views

(Psychology research) Is it appropriate or coherent to standardize these variables?

I am doing a project where I'm analyzing various lexical dimensions of speech from folktales from 10 countries. And the program, LIWC, returns a value for each category with that value representing ...
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16 views

z-score normalisation - how to achieve this for score combination?

I have read that to perform a score fusion from two different classifiers on two different datasets then the score must be normalised. I understand I can use z-score normalisation / max-min ...
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1answer
42 views

Reasons NOT to use standardised data in multivariate analysis

Question: Can you give any reasons/examples when it is more appropriate NOT to standardise continuous metric independent variables when performing multivariate analysis? Background: I am an undergrad ...
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59 views

Data normalization/standarization and comparing

I have a question related to data comparing. First of all, my dataset is composed by cities of the world. In this cities, we have a maximum of 24 tags that indicate what these cities are best for. ...
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1answer
46 views

How to standarise percent values 0 - 100%

I'm working on dataset that contains a variable from 0 to 1 (0 - 100%). Distribution of the variable differs depending on the context (defined by another variable). Depending on the context the ...
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12 views

normalization and rescaling definitions are mixed up?

in: https://en.wikipedia.org/wiki/Normalization_(statistics) it's written that rescaling(min_max_scaling) and standarization are types of Normalization what i see in alot of stackoverflow answers is ...
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25 views

Standardization and prediction on new data

As far as I know it is common practice to do standardization of variables before shrinkage or PCA, which are methods I intend to use on my model selection for a predictive model. But the problem is, ...
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1answer
25 views

What time of the day do I usually take my medication?

Suppose one makes a calendar recording the time a certain thing was done everyday, for example what time one took a certain medication, what time one woke up or what time one started exercising. ...
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17 views

Heteroskedasticity consistent SEs with Proc ROBUSTREG in SAS

We are using the Proc ROBUSTREG command in SAS to down-weight the influence of the outliers (mainly in the Y-direction). Furthermore, we wish to use heteroskedasticity consistent SEs and standardized ...
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1answer
19 views

Ranking submissions based on multiple judges

I have a situation in which we have 20 proposals and five judges. Each proposal is reviewed by three of the five judges, assigned to the proposal at random. Each judge scores the proposal out of ...
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1answer
68 views

Standardization in neural network online training

It is common knowledge that the inputs to a neural network should be standardized to have mean 0 and variance 1 (see this thread for example, or the LeCun paper). And as long as one does batch ...
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1answer
54 views

Use z-scores to determine the best strategy for airlines

Most airlines board passengers starting from the back of the plane and then working their way towards the front (after boarding priority classes and passengers). In an episode of Mythbusters, Adam ...
5
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1answer
94 views

Should the correlation PCA projection be computed on original or normalized samples?

Suppose we compute the correlation PCA of a dataset $X$ (with $m$ variables and $n$ observations) by first normalizing the input variables. That is: mean -> 0 and standard deviation -> 1. Let us ...
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27 views

When to scale or standardize data in regression

Many statistical software ask whether to standardize data or no: What is a general rule to when data should be standardized? Do we standardize categorical variables? Is there a difference in how ...
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1answer
48 views

Why doesn't standardization work in the linear regression?

I have a matrix containing the attributes of the item and their corresponding rating. All of the attributes are in the range of (0,1) and the rating is in [1,5]. I transform the range of rating to (0,...
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1answer
46 views

Variable standardization / scaling for PCA when all dimensions already have same scale [duplicate]

Often when PCA is performed on exam results where all variables (dimensions) have the same $0$ to $100$ scale, scaling is none the less applied. For different scales I can see the purpose of it, but ...
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26 views

What is the meaning of a t-statistic?

When working with a normal distribution, the z-score can be interpreted as the number of standard deviations from the mean a given value is. ($z=2$ means that $ x $ is 2 standard deviations from the ...
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24 views

Using trimmed means and Winsorized variances to compute standardisation of data

I am looking into the pros and cons of each normalisation technique for work and it got me thinking. What if I used trimmed means and the sqrt of Winsorized variances to compute the standardised data? ...
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17 views

Rescaling vs Standardization of features

Is there any general rule of thumb or any justified rule to choose whether to scale a dataset using Rescaling (for each feature, subtract the min value and divid by the max - min) or Standardization (...
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12 views

Comparison of regression coefficients between (nested) geographic regions

I would like to compare the effect of an explanatory variable (say X1) on a response variable (Say Y) between two geographic regions in which one is a sub-region of the other. For example, I am ...
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1answer
55 views

Standardized LASSO in R still has intercept

I understand the need to standardize variables when performing LASSO in R (I'm specifically using cv.glmnet, and setting ...
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1answer
28 views

Normalize all data before cross-validation or normalize every train part separately and use same properties for test part?

Suppose that we want use 5-fold cross-validation for a support vector regression(SVR) model. We should normalize total data before cross-validation process or we need normalize every train part ...
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25 views

What is the correct way of standardizing data when there are training, validation and test set [duplicate]

When standardizing data before training a neural network, say by subtracting the mean and then dividing by the standard deviation for each variable, there are several ways one could go about that and ...
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1answer
18 views

Best way to examine longitudinal data?

I had 20 patients come to clinic once a month for 6 months. At each visit we collected baseline data. We then gave the patients 3 different treatments to see the effects for each visit. Thus we have ...
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1answer
111 views

Normalization of count data of time periods with different length

I have count-data from two time-periods which differ in length. The event I'm counting is in both periods the same kind of event. Period 1 is 120 hours Period 2 is 48 hours At the end I have ...
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107 views

Is it a mistaken idea to use standardized coefficients to assess the relative importance of regression predictors?

There are various questions that speak to the relative merits of various methods of assessing the importance of regression predictors, for example this one. I noticed that in this comment @gung ...
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68 views

Standardization with mean/std or median/IQR?

I have a dataset with 10000 data points and 20 features. The features are not normally distributed (most of them have a generalized extreme value or burr distribution and all values are greater or ...
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1answer
79 views

Standardization before PCA with data in same units and similar interval? [duplicate]

We have 16 variables which are indices produced by calculations based on ratio (unitless in fact). Some examples of the ranges of our variables are (0.450-0.750), (0.000 - 0.800) and (0.000 - 1.000). ...
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1answer
46 views

Transformation of a Skewed Composite Outcome made up of 2 Z-scores?

I am running a repeated measures mixed model. For my outcome variable, I would like to sum 2 continuous variables, which consequently are both Z standardized in order to do so. However, my outcome ...
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1answer
39 views

Normalization vs Standardization for multivariate time-series

I'm using DTW as a distance measure for comparing two multivariate time-series. I want to be able to cluster data using DTW as distance measure, since time-series may be shifted, skewed. Since there ...
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40 views

How to standardise linear regression

I have a set of death rates (that range from about 0.1 to 0.5), a set of body weights (that range from about 2 to 80), and I want to calculate standardised residuals for the death rates after ...
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163 views

double feature value in ridge regression, coefficients change?

In ridge regression using unnormalized features, if you double the value of a given feature A (i.e., a specific column of the feature matrix), what happens to the estimated coefficients for every ...
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16 views

Method of standardization of essay grades from a number of graders

Basically, there is a group of us grading a few hundred essays. We divided the number up so each of us grade 50, assigning a score 0-100 given a rubric. However, there is still subjectivity in the ...
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19 views

Standardizing Continuous Predictors in a Model While Not Standardizing Categorical Predictors

I have a logistic regression model where I have predictors that are categorical (binary) and continuous. It makes sense for me to standardize my continuous predictors, as I am doing something similar ...
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17 views

Standardization of all variables and weighting of some variables for clustering

I am trying to segment a database based on certain variables. I understand that before i do start clustering, i should standardize all the variables. This can be done by Z score or other methods. ...
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37 views

Is z score transformation necessary before running a mean comparison statistic?

I have 5 sets of scores from 5 different tests given to some students (let’s say group A) across 5 sessions (i.e. within-subject design). The first test (i.e. pretest) has 33 items, the last (i.e. ...
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45 views

Centering and scaling skewed distributions

I have a dataset where the features are skewed (non normal) distributions. My preprocessing pipeline consists of the following steps: Missing values imputation Centering and scaling (zero mean and ...
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26 views

Normalization by z-score + range [0,1]

I am trying to normalize my dataset for further analysis. I have several data coming from different subjects, so I have first applied z-score normalization to each variable of each subject in order to ...
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1answer
29 views

Do I apply normalization per entire dataset, per input vector or per feature?

One of the ways to standardize input data for Neural network training is: \begin{equation} X = \frac{X - mean(X)}{std(X)} \end{equation} However if I have have $n$ training examples which have each $...
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2answers
119 views

When to normalize data in regression? [duplicate]

Under what circumstances should the data be normalized/standardized when building a regression model. When i asked this question to a stats major, he gave me an ambiguous answer "depends on the data". ...
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2answers
88 views

Use a combination of grand mean and group mean centering to standardize variables

I'm using cluster analysis to examine profiles of three variables, X1, X2, and X3. Because ...
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3answers
62 views

Working with ratios: standardizing problem

I have a dataset, let's say of counts of apples and oranges. I would like to have a metric that equally reflects the ratio of apples to oranges but if I simply use the ratio: apple count + 1 : ...
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63 views

Logistic Regression is not working when I'm standardizing the data

I am implementing Logistic Regression for the Fisher's iris data set in Matlab using Newton's method for parameters estimation. Those are the dimensions of the matrices: Measurements (Data matrix):...
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0answers
6 views

summarize scores to the same metric without the raw data

I would like to have a mean z score or standardized score for 12 tests each of which have different scales. I only have access to the mean, standard deviation, 95% CI's, and Q1, Q3 for the raw data, ...
0
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1answer
9 views

Comparing scaled error

Say I have a regression technique (in my case I'm using ANNs) I am tuning on a data set. Say I am minimising a loss function that is not scale free, such as mean square error. Usually I would ...
0
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1answer
330 views

DCC GARCH model diagnostics in R

I have fitted a DCC GARCH model to my multivariate financial data. So, now I need to check the fitted model by using the standardized residual and its squared process. A good fitted model should have ...
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29 views

Should I centre or standardise variables in a linear mixed model analysis?

My study is looking at skin lesions in pigs. I have 2 partially cross-classified random factors (weaning pen and finishing pen) and several predictor variables. I have centred pig weights by pen ...