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

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10 views

Standardizing variables at item or index level: Does it make a difference?

I'm running some multiple group CFA models comparing covariance structure by race/ethnicity and have survey data from 6th, 8th, 10th and 12th graders. My supervisor has told me to combine 6th and 8th ...
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18 views

Proper use of the coefficient of variation

I have a variety of samples, each with a different standard deviation and mean. The coefficient of variation $CV$ = ${\sigma} / {\mu}$ defines the amount of variation in a population or sample around ...
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2answers
176 views

Does feature standardization always make sense?

I wonder if feature scaling like this makes always sense for neural networks: Let $T$ be the training set and $x_i \in \mathbb{R}^n$ with $d_i \in T$ be the feature vector of $d_i$. Then add another ...
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21 views

standardization to obtain unit variance

I've come across some papers in where certain forecast errors are standardized to have unit variance. Unfortunately that's the only information they provide and I have no idea on how to ...
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1answer
32 views

Question about standardizing in ridge regression

Hey guys I found one or two papers which use ridge regression (for basketball data). I was always told to standardize my variables if I ran a ridge regression, but I was simply told to do this because ...
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1answer
61 views

How to standardize data

I have the test scores of two groups, say A, and B. And the former consists of 186 individuals whereas the latter only has 100. The test scores range from 1 to 12, and because group A has more people, ...
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1answer
55 views

Standardizing before/after/at all when using multi-class LDA for pre-processing step

If a multi-class Linear Discriminant Analysis (or I also read Multiple Discriminant Analysis sometimes) is used for dimensionality reduction (or transformation after dimensionality reduction via PCA), ...
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6 views

Standardising data within-subjects when analysing distributions

Analysing behavioural data, Spivey, Grosjean and Knoblich, (2005) wanted to show that their results came from a unimodal distribution, rather than from averaging over subpopulations in a bimodal ...
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11 views

Weighting, standardize, transforming data before for Multivariate ANCOVA

My question is in regards to data manipulation prior to Multivariate ANCOVA. My research focuses on crustacean eggs. The model involves a covariate and 2 x independent variables and 4 dependent ...
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1answer
26 views

Standardizing single coefficient in multivariate analysis

I have panel data and for the I have a following equation $$ logY = \beta_1 + \beta_2 logX + \beta_3 m logW $$ Problem is with $\beta_3$ coefficient. Since m is outside the log and it is a very ...
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1answer
44 views

Feature Normalization/Standardization before or after Feature Selection?

Should the process of feature normalization/standardization be done before or after the feature selection process?
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1answer
19 views

Does a time-series have to be stationary before you calculate a z score or t score?

It's been a long time since basic statistics. I have a financial time-series that exhibits exponential growth. Before I standardize, do I have to make the time-series stationary? Before I ...
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27 views

Centering vs. Standarizing which one is better? [duplicate]

Two approaches have been proposed in order to overcome the issue of multicollinearity if we have interaction variables which are mean centering and standardizing (z scores). You can check No.2 in this ...
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1answer
43 views

Intercept from standardized coefficients in logistic regression

I have fit a logistic regression model with original y and standardized x variables. Slope coefficients can be easily converted back to their original scale by $\beta^*_j/\sigma_{x_j}$ where ...
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23 views

How to standardize a variable an its power term?

In an regression analysis it is sometimes valuable to introduce power terms as predictor variables. Age is a good example in the social sciences. I know there is an general debate about introducing ...
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2answers
79 views

Standard method for calculating contribution of individual variable to outcome

I'm looking at the change in vote shares for an election between two periods. I'd like to say something about the contribution of one variable in particular towards the election swing I document. I'm ...
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1answer
35 views

Interpretation with training and test set with standardized variables

I've standardized all the variables (even the response variable) and then I've split my data into a training and test part. And for example, I've got the following model based on my TRAINING set: y = ...
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1answer
45 views

Standardizing feature vectors for regression

Suppose I have a data set with the following structure: Each row of the data set indexes a town. The first column/feature variable is the total population while the other feature variables include ...
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1answer
64 views

Rescaling exponentially distributed variables before clustering?

I want to cluster data that contains binary variables, exponentially distributed (power law) variables, and normally distributed variables. I'm considering preprocessing the data in the following way ...
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16 views

Confused about GARCH innovation distribution

I'm a bit confused about the error distribution of GARCH models. I understand that several standardized distributions (i. e. expected value = 0, variance = standard deviation =1) can be used, for ...
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1answer
68 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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2answers
566 views

What's the difference between standardization and studentization?

Is it that in standardization variance is known while in studentization it is not known and therefore estimated? Thank you.
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18 views

Why should the feature be standardized before feeding to the neural network algorithm [duplicate]

Before feeding the features to the neural network algorithm, we have to standardize these features. Why? This is an interview question asked in my recent interview for a data scientist. Can ...
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25 views

How to compare pairs of coefficients within a glmm with binomial error

I have a generalised linear mixed model with 34 explanatory variables (over 130,000 observations for each). 10 of these variables are different unprotected habitat types, and another 10 are the same ...
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12 views

I have survey data where people respond to multiple items. I want to find the avg and SE on each item, controlling for within subject variation.

I have survey data from 650 respondents. Each participant rated 11 items on the same scale. I would like to know, at the population level, how the average of each of these items compare. For ...
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1answer
48 views

Building a ML ordered logit regression model

I am building a ML ordered logistic regression. First of all, I really don't know if this is the best way to fit a model to my data, as I am not too confident in ML ordered logit regressions, compared ...
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1answer
20 views

Conversion to Standard Normal with Probability

Good day everyone, I am currently working on a self-study question: Question The number of viewers of a television show has a mean of 29 million with a standard deviation of 5 million. Assume ...
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26 views

One-out-of-K coding and standardization

I heard from an university course that a normal method for turning categoric variables into binary variables was to simply create a binary variable for each category (one-out-of-K coding). However, ...
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1answer
44 views

Confused about standardization

I read a lot on the web, but I am still not sure whether I understood completely when we standardize the data (so that it is zero mean unit variance). So, let's say that I have a set of genes and ...
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67 views

Outlier removal and standardization of variables

In a multifactor model of stock returns, I am considering several variable $X_1$, $X_2$, ... , $X_n$ as explanatory variable. However, before including the variables in the model, I would like to: ...
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125 views

Standardizing count variables in panel data with overdispersion - R or Stata

I'm running a regression where the dependent (response) variable is a highly dispersed (slightly zero-inflated) count and the explanatory (independent or predictor) variables are continuous, counts as ...
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1answer
35 views

Could standardizing an independent variable cause the t-statistic of the OLS estimate to change?

Lets say we are looking to estimate the following standard OLS regression: $y_{i} = \beta_{0} + \beta_{1}*X_{i} + \beta_{2}*Z_{i} + \epsilon_{i}$ and that we choose to standardize $X$ as: ...
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17 views

Standardized coefficients and IV method

In a multivariate regression, suppose we want to calculate the metric coefficients from the standardized ones. Is the method (standardized coeffcient times standard deviation of the dependent ...
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71 views

Can you combine z scores from similar but non-identical populations?

Suppose you have a group of people estimating the heights of trees. Suppose you have many different types of trees, some trees with a very low height, and others that are very tall. Suppose each ...
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45 views

Scaling/Normalisation or Standardization

I'm working on SVM and ANN classification tools. In order to improve the classification accuracy, I want to know the best or the recommended data-preprocessing, is it scaling/normalisation or ...
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40 views

Standardizing variables for k-means?

I only have two variables and they are on the same scale. However, the variance corresponding to the first variable is approximately 0.609, whereas for the second variable is 0.154. So my question is ...
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1answer
67 views

Comparison of subpopulations: do I need normalisation?

I have a population of people. Each person has one of three characteristics, say X, Y or Z. I want to compare other characteristics of these people, using the characteristics X, Y and Z as a ...
2
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54 views

multiple linear regression with normalization - how to get non-scaled full covariance matrix

I am doing a quite complicated multiple regression modelling in physics and have a problem how to got back to covariance matrix for non-normalized parameters. I don't know how to calculate the error ...
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2answers
146 views

Z-scores, standardized tests and population means

I have been using z-scores by subtracting the mean (and then dividing by the SD) of the sample, whereas I recently read they actually need to be the population mean and SD. Assuming you are ...
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0answers
64 views

Composite Scores and Standardized Composite Scores t test

I have a set of survey data related to 20 survey questions. Each of these questions represent a variable (Q1, Q2,......
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2answers
68 views

Standardizing inputs for CART

I know I do not need to standardize the predictor variables before applying CART but would there be any adverse effects to doing it anyway? I'm comparing CART to a linear regression where I did ...
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18 views

Standardization of data during multilevel analysis

Recently I obsessed about standardization of scores. I am looking into statistical literature to see if standardization of data is OK or not. a brief about standardization: ...
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30 views

About Standardizing Variables

Before data analysis, by $\frac{(X-mean)}{std}$, so the new variables have mean 0 and variance 1, and then compare different variables since then they are on the same measure scale, my question is, ...
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1answer
189 views

Is standardisation before Lasso really necessary?

I have read three main reasons for standardising variables before something such as Lasso regression: 1) Interpretability of coefficients. 2) Ability to rank the ...
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116 views

Variable Transformation using Cumulative Distribution Function (CDF)

Consider two different data time-series, Data1 and Data2, expressed using inhomogeneous scales (units). Each of these two data series is itself a weighted-average of a bunch of standardized ...
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29 views

what can be inferred from the error plot of my classifier?

I am working on a classification task where I use 12 features. My training set has 400 samples of positive data and 2000+ samples of unlabelled data. While testing has 34 positive samples and 999 ...
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1answer
29 views

Standardising the weights generated from feedforward back propagation NN

I have binary data input to NN. The weights generated by NN are not normalized, i.e., the weights are not the same for every run of the algorithm. How to standardize these weights?
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59 views

Running standardized/unstandardized regression equation on SPSS

I am working on a regression assignment using SPSS. I have raw, centered, and z scores for the data. I already regressed the DV and IV and see the unstandardized and standardized coefficients under ...
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1answer
52 views

Interpreting standardized mean centers in a cluster

I created a $k$-means with 3 clusters. Some of the variables had a big scale, so I used a $z$-score to standardize them. The others (mostly dummies), I left as is. Now, when I create the table of all ...
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36 views

prerequisites for z-standardization

I tried to search for an answer to this but I was not successful in finding a good one. I wanted to compare data from two modalities together (an EMG reflex and self-rating). I found that in the ...