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

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6 views

e1071: does the tune function do the scaling?

I'm using tune to choose the optimal gamma and cost hyperparameters for a RBF SVM. As feature scaling is essential, my question is: does the tune function do the scaling?
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41 views

How to name the concept of the mean shift divided by the standard deviation

In the context of a paper dealing with Statistical Quality Control, I am defining and using the concept of the mean shift divided by the standard deviation of a (normally distributed one-dimensional) ...
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1answer
22 views

Unstandardize the slope of standardised variables in a linear regression

If I standardize my dependent and independent variable, and run a linear regression between them, the slope estimate which I have will be standardised. The variables were standardised by subtracting ...
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13 views

Should I standardize or rescale with polynomial regression as alternative to difference scores?

I am working with a model that uses polynomial regression combined with response surface modelling as an alternative to difference scores in regression: ...
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0answers
11 views

Standardization and autoregressive process

If I have an autoregression with an exogenous variable and standardized the exogenous variable to better interpret the coefficients, can I standardize the dependent autoregressive component also so ...
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1answer
24 views

z-score and Normal Distribution

I have what is probably a pretty stupid question but for whatever reason I have not been able to find an answer so here goes.... It's my understanding that a z-score can only be calculated and ...
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1answer
24 views

Is standardisation and normalisation of data required before clustering when I have only 1 variable?

I have a data with only 1 variable. I need to use K-means clustering on it. Do I need to apply normalisation and/or standardisation on the data?
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6 views

transforming of standardised effect size in MuMIN package

I ran the following model ...
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1answer
36 views

lmer: standardized regression coefficients

I have analyzed some data (the exact nature of which, I assume, is irrelevant for this question) using linear mixed effects models with the lmer() function from lme4. There has been at least one ...
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0answers
26 views

How to standardized my data

I require to standardize my data before conducting any statistical tests, but I don't know how to do it or what procedure would be more appropriate. I am running a number of statistical tests to test ...
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1answer
65 views

Standardized coefficients for linear models with numeric and factor variables in multiple linear regression using scale() function in R

I have on question regarding standardized coefficients (beta) in linear models. I have already asked one question here. From the answers I assume that I should use R's ...
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0answers
24 views

standardization within time series and across groups (nested data)

I read through the previous threads concerning standardization of variables, but unfortunately have not found an answer whether it is justifiable or necessary to z-standardize values across groups ...
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45 views

z scores, highest percentile ranking, different distributions

Let a value $x$ have a z-score of (say) $+0.10$. With respect to which distribution(s) can $x$ have the highest percentile ranking: normal, positively skewed, or negatively skewed?
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1answer
22 views

Symbol to indicate normalized or standardized variables

Is there a symbol to indicate that variables have been standardized? For example, if I have 2 different scoring functions Score1 and Score2. Let's say I want to form a combo score and show that the ...
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1answer
34 views

Standardized coefficient for a categorical variable in logistic regression

I would like to rank independent variables in a logistic regression model based on relative importance. I've read about standardizing the variables prior to entering them in the model. So in this ...
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0answers
17 views

R- yaimpute - standarize value before KNN for imputation

I need to impute data before running a logistic regression. I'm trying the package yaimpute but I realized that it doesn't standarize before imputing. I created a sample matrix to view so: ...
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0answers
9 views

WHO Z-scores for bench-marking child growth: usage and interpretation

I have a data set which consists of two disjoint groups of children. I would like to compare the nutritional statuses of the two groups. Luckily, I have some anthropometrical measurements of the ...
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0answers
29 views

How to interpret the regression slope of standardised variables

my y variable is crop production (in kg/ha) and x variable is rainfall (mm). In a linear regression, if the slope is 0.5. I would say, 'if rainfall increases by 1 mm yield increases by 0.5 kg/ha.' ...
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3answers
46 views

Compare influence of same set of independet variables on two different dependet variables

I'm currently doing two multiple linear regressions. Each of them with the same set of predictors (measurements for real estate quality) $X_1,...,X_n$, but with different dependent variables (one of ...
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0answers
15 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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0answers
68 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
187 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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0answers
32 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 ...
2
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1answer
55 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 ...
2
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1answer
145 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, ...
2
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1answer
108 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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0answers
15 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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26 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
29 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
66 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
23 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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0answers
28 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 ...
3
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1answer
65 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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0answers
24 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 ...
2
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2answers
88 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
52 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
54 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 ...
3
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1answer
108 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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0answers
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
84 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
668 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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0answers
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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0answers
37 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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0answers
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
58 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
24 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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0answers
60 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
48 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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0answers
89 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: ...
2
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0answers
190 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 ...