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

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5
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1answer
80 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 ...
3
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0answers
22 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 ...
0
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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 ...
2
votes
1answer
42 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 ...
1
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0answers
25 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 ...
0
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0answers
17 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? ...
0
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0answers
14 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 ...
1
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0answers
7 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 ...
1
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1answer
40 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 ...
0
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1answer
16 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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0answers
24 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 ...
0
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1answer
15 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 ...
1
vote
1answer
88 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 ...
6
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0answers
57 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 ...
0
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0answers
50 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 ...
0
votes
1answer
68 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). ...
0
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1answer
41 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 ...
0
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1answer
26 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 ...
0
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0answers
35 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 ...
2
votes
0answers
76 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 ...
0
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0answers
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 ...
0
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0answers
11 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 ...
0
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0answers
14 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. ...
0
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0answers
32 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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0answers
36 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 ...
1
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0answers
13 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 ...
1
vote
1answer
23 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 ...
4
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2answers
95 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". ...
0
votes
2answers
57 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 ...
1
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3answers
59 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 : ...
0
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0answers
56 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 ...
0
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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
votes
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
votes
1answer
200 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 ...
1
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0answers
26 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 ...
0
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0answers
58 views

Q-Q plot standardized log returns vs log returns

When working with financial returns and detecting heavy tails with EVT, Q-Q plots can be used to make assumptions of the normality of the data(e.g.). Using standardized log returns in qq plots one ...
1
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0answers
25 views

'Z-standardizing' data based on Poisson process

Hello all this is my first post on Cross Validated, so please let me know if it is not in an acceptable form. I have been attempting to analyze a data set where I have a Bernoulli process that is ...
1
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2answers
129 views

Should I ever standardise/normalise the target data/ dependent variables in regression models?

After standardising the explanatory variables the difference in magnitude between the explanatory variables and the target data is ~3 orders of magnitudes. I want to know if transformation of the ...
0
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0answers
12 views

Should I be using Raw or T scores in my mixed ANOVA?

My data that tests infants at 4 time points on the same measure (Motor skills). There are also 3 groups of infants (typically developing, atypical and unsure).I want to use a mixed ANOVA to look at ...
0
votes
1answer
112 views

Feature standardization for convolutional network on sparse data

I am preprocessing input data for a convolutional network (ConvNet), which is trained with SGD. For instance, see this quote from Ilya Sutskever (A brief overview of Deep Learning). It is ...
5
votes
2answers
98 views

How do regression results change after standardization, as a general rule?

Based on the simulation below, it appears that standardizing all variables in a data set affects OLS results in the following ways: Coefficient estimates change Standard errors change P-values ...
1
vote
1answer
36 views

Informativeness of t-score?

My organization recently did a morale survey. Results were given as t-scores. I had never seen that before, so I embarked on a web journey. I found a very similar survey. My question isn't about the ...
0
votes
1answer
25 views

Reference for standardizing non-normal variables for comparison

I need a reference to justify standardizing non-normal data. I will first explain what I am doing. I had a survey with ~30 questions. The answers to the questions were numeric; the range of possible ...
2
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0answers
79 views

What to do with categorical data when calculating standardized z-scores?

I have numerous environmental variables I'd like to correlate to some tree species data. The environmental variables vary greatly in scale, so I'd like to standardize each by calculating standard ...
0
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0answers
12 views

Lasso - standardize y or only x? [duplicate]

In lasso, I am standardizing the input, x. What do I need to do with the output, y? Are any transformations necessary? Only centering? Both centering and scaling? This question is not a duplicate ...
0
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1answer
28 views

Normalizing a large set of ratios

I have a problem that has been causing headaches. To set up the problem, here's what I have. Bear with me, since I'm trying to clarify the problem as much as possible: A large set of personnel These ...
0
votes
1answer
63 views

Is it possible to normalize data by different group leaders separately?

I have a dataset that contains different states of a country. In every state there are different companies and one company in every state is manager of other companies in that state (other companies ...
1
vote
1answer
64 views

Standardizing or normalizing count data

I have a dataset where I counted the number of a species in different environments and grouped it into different categories ranging from 0 to 5. 0= no occurrence; 5= very high occurrence. All ...
1
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0answers
39 views

Power transform before aggregating data: benefits and risks

I have several physiological recordings from different users, for example heart rate. I would like to aggregate these time-series into a single "metric". Let's say that I want to apply the mean ...
1
vote
2answers
92 views

Standardized estimates give different p-value with a glmer/lmer

I have a large data set where I relate the response variable to multiple explanatory variables; since I have different areas I have also included a random factor. The response variable is binomial ...