Mathematical re-expression, often nonlinear, of data values. Data are often transformed either to meet the assumptions of a statistical model or to make the results of an analysis more interpretable.

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23 views

Interpretation of log(1 + var) transformed predictor

Interpretation of log transformed predictor neatly explains how to interpret a log transformed predictor in OLS. Does the interpretation change if there are 0s in ...
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3 views

Resouces, tutorials or courses for data/text manipulation [on hold]

Online and free course or complete tutorial for data/text manipulation?
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4 views

Choosing a tech stack for data/text manipulation [on hold]

What is the most powerfull technonology stack for huge data/text manipulation, python, R or Bash tools (sed, awk, cut, tr, etc). What are the pros and the cons of which one?
3
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1answer
87 views

Transform normal distribution to skewed distribution without changing its support

I've found many questions and answers about transforming skewed distribution to normal. This question might arise because the simplicity of working with normal data. But, is there any function that ...
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36 views

Downside to scaling and centering?

Bottom line up front: is there any reason not to center and scale continuous variables prior to model fitting for the sake of conducting model comparison? I'm conducting a model comparison on a large ...
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0answers
41 views

T tests on proportions - Wrong, but how wrong?

In psychology, and probably a number of other disciplines, it's common practice to test between-groups effects on a binary variable, such as accuracy, by aggregating data within participants, and then ...
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1answer
20 views

What is the distribution of a normalised (scaled) poisson distribution?

I have 5 groups of very different sizes. I want to know if various attributes are the same for the groups when I have corrected for the differences in size, e.g. ...
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0answers
19 views

Help in handling heavily naturally skewed variables [closed]

I am doing some statistical analysis for my thesis project (not a statistics degree) and I hoped to get some help from you as the statisticians in my uni couldn't help me much. The analyses that I ...
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1answer
44 views
+50

Transformation among power-means

It is well-known that arithmetic and geometric mean are strongly related via logarithmic transformation, i.e. if we take arithmetic mean of logarithmic-transformed values we get the same as if we take ...
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15 views

Simple Path to Route Algorithm [closed]

I'm currently conducting research into subway paths, but stand in front of a problem, with no programming knowledge and an extremely short time-limit. Probably the question I am asking is trivial, ...
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0answers
24 views

Rewriting linear equation

So I have a linear equation produced in R: logBodyWt = -1.08968 + 1.22496 x logBrainWt And that's all groovy but there is a question in a module which asks me to "Rewrite your model as a non-linear ...
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1answer
42 views

Transforming a Random Variable's distribution to Normal using Z-Scores

I have a random variable and many observations of that variable. The random variable is not normally distributed; its distribution is unknown. However, to analyze this variable and construct a time ...
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1answer
29 views

GLM or arcsine and two-way ANOVA

I am trying to analyse data on how long deer have been vigilant in a 2 minute observational period and how this varies between males and females and also whether they were in the centre or edge of the ...
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1answer
161 views

Interpreting regression with transformed variables

I have conducted a linear regression analysis with four variables. The response, say $\#$ of eggs per 2000 hens, and one of the predictors, say temperature change, are highly skewed. I have hence ...
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1answer
41 views

What is the best data transformation for absolute zero inflated distributions?

I have 3 variables with the following distributions: What is the most appropriate transformation to make them as normally distributed as possible? This data is absolute zero inflated.
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17 views

Compare Procrustes values

I have two sets of spatial data which underwent a transformation. I'd like to compare the effect of the transformation on two sets of data to test the hypothesis that the transformation had a larger ...
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2answers
465 views

Transforming Data: All variables or just the non-normal ones?

In Andy Field's Discovering Statistics Using SPSS he states that all variables have to be transformed. However in the publication: "Examining spatially varying relationships between land use and ...
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4 views

R: Running sum of changed column values within groups [migrated]

I have data that looks like this: ...
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2answers
25 views

How do I evaluate two models that have different (transformed) DVs?

I'm testing two different models that differ only in terms of how the dependent variable has been transformed (e.g., Model 1 DV = Y, Model 2, DV = √Y). I've read that AIC is not appropriate here -- ...
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27 views

So survey data cannot be normal distributed?

I am analyzing a data from survey. The data is from a 2X2 between subjects experiment design with 45 subjects in each of the four conditionsThe questions are based on a 5-point or 10-point scale. ...
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76 views
+50

Standardize VS centered variables

I have found many useful posts about standardized independent variables and centered independent variables on stats.exchange.com, but I am still a bit confused. I am asking you an evaluation of what ...
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32 views

Practical beginners resource for building a dynamic OLS model

I need to model the current account balance of a country. The regressors are the real effective exchange rate, the domestic GDP and the GDP of the world. I am using data for 30 years (in logs). It is ...
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0answers
33 views

Untangling lump samp panel data?

Edit: Context: I am estimating persistence analog Heckman (1981) based on firm level data. The endogenous variable is the distribution amount of profits directed to the owners. To estimate ...
2
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1answer
18 views

One-mode network (data transformation)

I'm looking for a solution to perform network analysis among my data set. My database is shaped like this : Table 1 : ...
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0answers
23 views

Using the linear equation with log transformed data

If I have log transformed axes and then produce a nice linear regression model. How do I use the equation of the line? i.e. Can I use my raw data $x$ values to predict real values for $y$? Is the ...
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1answer
163 views

How can you convert a gamma distribution into normal distribution? [closed]

A region has 200 stores served by a single distribution center. Demand of X during lead time (the time interval between order placement of X and arrival of X) at each store is forecasted to be gamma ...
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24 views

How to model “aggregate” dependent variable in case of variable transformation?

Background: I have a panel data set consisting of dependent variable $y_{i,t}$ and several independent variables $x_{j}$, where $i$ indicates observation (ID), $j$ serves as dependent variable index ...
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35 views

Transformation of variables to fulfill normality assumption before GAM

We are running a GAM with highly skewed (and positive data) both in the dependent and in the independent variables. We have chosen to transform both the dependent variable (cubic root transformation) ...
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3answers
105 views

Mean centering - before regression or observations that enter regression?

I am using Stata 13 to estimate a simple model with interaction terms. To give the coefficients a meaningful interpretation at zero, and to avoid multicollinearity, I am mean centering variables. I ...
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1answer
19 views

Calculating percentage difference between maximum and current value

I am having a set of calculations say variable x and a maximum value max(x). I want to calculate percentage difference of variable or observation xi from max(x). What can be the most suitable ...
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61 views

How to backtransform data that has been log transformed in order to report raw values for ease of interpretation?

I have run some lme4 analyses on reaction time data in R, with RT being the main outcome variable of interest, which I first log transformed due to non-normality ...
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14 views

Complicated joint distribution with constraints on the ratio

I'm trying to create random draws of pairs of numbers based on desired distributions of the numbers and the ratio of the two numbers. Let me explain in more detail, although I apologize if my notation ...
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1answer
50 views

Daily data, different dates

I have downloaded two different daily data sets, both for the same period. Together I want to use them to construct data for another variable. However, the problem is that the dates do not exactly ...
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2answers
46 views

Square of gamma random variable [duplicate]

If i have a random variable with distribution $X \sim \Gamma(\alpha,\beta)$ then what would be the distribution of $Y = \lambda X^2$ (with $\lambda$ a scaling factor)? Can I say that $Y$ will follow a ...
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0answers
23 views

Natural logarithm transfomation and zeroes [duplicate]

I am using Stata 13 to estimate a simple regression. Given a rather positive skew of a few of my covariates, I figured to ln-transform the variables. However, I have a substantial amount of zeroes in ...
4
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1answer
167 views

Data augmentation techniques for general datasets?

In many machine learning applications, the so called data augmentation methods have allowed building better models. For example, assume a training set of $100$ images of cats and dogs. By rotating, ...
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78 views

Comparison between regression of $a = bc^t$ and $\log a = \log b +t \log c$

This question is more qualitative then about the maths behind the equation. Variables: a = month (1, 2, 3, ) t = shipments of a product in that month You wish to derive the relationship between $a$ ...
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1answer
76 views

How to interpret regression coefficients when the dependent variable is square root transformed? [duplicate]

I have problem with interpreting the OLS regression result with the dependent variable square root transformed when doing difference-in-differences analysis. Our regression model is: $$ Y = β_0 + β_1 ...
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0answers
13 views

Does clustering of data in added variable plot merit transformation even without non-linearity?

I'm running a regression and when examining the added-variable plot for one of my independent variables (DBLB), the data appears to be clustered to the left as below. A Box-Tidwell transformation ...
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12 views

Analysis with different input and output data granularity

I am presented with a peculiar problem. I have continuous sensor data that is recorded at every 10 minutes as input variables and psychological data through a survey taken every 1 hour as output. I ...
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1answer
53 views

Is it possible to calculate Q1, Median, Q3, StDev from already aggregated data?

We have data that will get aggregated per hour into the following values Q1 Median Mean Q3 Standard Deviation Max Min Count of Values So the data will look more or like this in the end. ...
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19 views

How to determine the number of employees in a business when sources are inconsistent?

I am analyzing a business survey data. I am interested in the total number of employees of each firm. Specifically, I am interested in: The total number of employees in a specific city, and The ...
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0answers
35 views

Interpreting level-level models with units in %

I have a model where the dependent variable is GDP growth in (%). I regress this on a my variable of interest, wine sales ($). Do I have a level-level model? Growth = a + Bwine + u How do I ...
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0answers
16 views

Is it possible and useful to determine the Z-score for arcsine transformed-data

I am currently analyzing flow cytometric data of healthy individuals and patients. I have the frequencies/proportions of several cell subsets in the blood of these subjects and now I want to determine ...
3
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1answer
61 views

Rank versus Box-Cox transformation

I'm attempting to assess the relationship between two quantitative variables, but the DV is highly skewed (and so are the residuals). I work among biologists who tend to favor non-parametric ...
0
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1answer
37 views

Chi-Square transformation on a partially unknown matrix

This question is a follow up to Hellinger transformation with relative data. I want to chi-square-transform my species abundance table, which represents only a fraction of the total species table. I ...
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1answer
34 views

2 factorial experiment (2 by 3). DV is NOT normally distributed

I just conducted an 2 factorial experiment that has 6 conditions (2 by 3). Specifically, my design is: IV1 = prior positive information (positive in A domain vs. control vs. positive in B domain) IV2 ...
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1answer
82 views

Hellinger transformation with relative data

It is my understanding that the Hellinger transformation is basically the square root of relative abundance data (if rows are samples). However, my row sums do not represent the total community (I am ...
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0answers
28 views

log transform response variable and linear relationship

If I log transformed my response variable, I know that the relationship between the response and the explanatory variables stay the same, but why is this so? Is it because log is a surjective ...
0
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1answer
77 views

Box-Cox transformation of dependent variable only

The function powerTranform from the "car" package in R mentions the following code for Box-Cox transformation for multiple regression: ...