# Tagged Questions

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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### Analyzing within subjects time-limited factors

I have 2 x 2 x 2 mixed design with two between subject factors (sex, organizer) and one within subjects factor (task). The last factor has values for task 1 and task 2. Both tasks were timelimited, 3 ...
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### How can I estimate theta for the inverse hyperbolic sine transformation?

I would like help with R code to estimate theta for the Inverse Hyperbolic Sine Transformation. This transformation is useful to transform skewed data that contain negative values or zeros. There ...
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### How to calculate percent deviance explained on square-root-transformed dependent variable?

I have a multiple linear regression model with a square-root transformed dependent variable. I want to report % deviance explained for each parameter. I assume I need to back-transform in some way, ...
119 views

### How to map a trajectory to a vector?

I have a series of data points in this form (timestamp, lat, long) for a set of users. Each user has a trajectory when he travels from point A to point B. There might be any number of points from A to ...
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### How to adjust measured values depending on control values?

I have taken 20 photographs. Each photograph contained a museum specimen of a bird and a colour chart. In each photograph, I measured the brightness of a specific part of the bird's plumage and the ...
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### Nonlinear regression: best transformation when getting very different parameter estimates

Disclaimer: Statistics is not my strong side, so if my question is nonsense I apologize. I'm a beginner, but really wanting to understand this. My question is: why do I get so widely different ...
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### To log or not to log? [duplicate]

I am working on industrial output data and running a lot of tests for it, before I proceed to make an ARIMA model for it. Before I do that, I need to decide whether or not to "log" the data. I am ...
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### how to Normalize data(with noise) into 0-1 range good scale in mean and variance?

i have a matrix data. Perhaps some data in one cluster and another in some cluster. data scale is between [0-1000](just example). and i want to normalize into [0-1] and good in mean and variance. it ...
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### R: Replace 0 in one data set with values from another [migrated]

I have data that has produced $0$ for the $User$ $Rating$ when the regression fails to converge. I want to replace these $0$ with the $User$ $Mean$ value that's in a different matrix. I have the ...
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### How to analyse a risk assessment questionnaire where each risk is rated for both probability and impact?

I would like your opinion on how to analyze a questionnaire on risk assessment in construction projects. For each question, concerning a specific risk for the project, there are two answers: An ...
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### Log transformed variable and main effect

I'm dealing with linear regression with a continuous outcome. Due to suspected non-linearity in one of the covariates (via scatterplot) I tried some possible transformations of the independent ...
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### Why is gender typically coded 0/1 rather than 1/2, for example?

I understand the logic of coding for data analysis. My question below is on the use of a specific code. Is there a reason why gender is often coded as 0 for female and 1 for male? Why is this ...
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### Regression to predict probability - what transformation to use?

I am working on a project where the training labels are given to me as a probability value in the range [0,1]. My first approach was to fit a simple linear ridge regression to predict the ...
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### Interpreting standardized betas with log-transformed dependent variables

I've run a multiple linear regression using standardized Betas and a log-transformed dependent variable; the latter transformation is primarily for better approximating linear regression assumptions ...
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### How to derive variance in data tracked over inconsistent (irregular) time intervals?

Background (skip if tl;dr) The close votes review queue at Stack Overflow looks pretty hopeless. I'm holding a weekly hour-long chat room event where users can congregate to review close votes ...
2k views

### How to interpret regression coefficients when response was transformed by the 4th root?

I'm using fourth root (1/4) power transformation on my response variable, as a result of heteroscedasticity. But now I'm not sure how to interpret my regression ...
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### Alignment and comparison of two unimodal and one uniformly distributed datasets

This question is similar to the following question: Normalize 3 irregulary distributed datasets and make their datapoints statistically relevant to each other describes similar problem, but is more ...
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### What are the assumptions of negative binomial regression?

I'm working with a large data set (confidential, so I can't share too much), and came to the conclusion a negative binomial regression would be necessary. I've never done a glm regression before, and ...
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### How to combine unbound variables with very different frequency distributions?

I want to combine three unbound variables. Each variable is the score provided by three different algorithms. Each algorithm predicts the likelihood (score) that a specific interaction between two ...
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### Transform and then fit in linear regression instead of using logistic regression

This is something I have read from the GNU mailing list: I retract my objection (sort of). I was thinking of the idealized maximum log-likelihood objective function, for which the ...
2k views

### Logistic regression with an log transformed variable, how to determine economic significance

I am using a logistic regression model with continuous independent variables and two log transformed size variables (total assets and total deposits). My question is how to interpret the results and ...
1k views

### Whether to use original or reverse coded items in factor analysis?

I am currently analyzing data from a 34-item Likert scale. I already recoded the negatively stated variables in SPSS as different variables. I'm about to do a factor analysis. Should I use the ...
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### Displaying fine variation across multiple orders of magnitude

I have a sequence of numbers that grows super-exponentially: 0.993, 0.999, 1.037, 1.054, 1.195, 1.55, 2.953, 15.369, 815.687, 26492.118 I'd like to be able to ...
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### Derivative of the transformed explanatory variable

I have an explanatory variable that is transformed as suggested in footnote 25 of the article as follows (the explanatory variable is continuous and can take negative, zero or positive values) ...
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### data-transformation for multi-state analysis using traminer/mstate

I am trying to estimate a multi-state model and am following the setup in the book by Mills (2011). The research units can go through different states a, b, c, and d. The research units can move ...
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### Slope error after transform?

I have a slope $b = 0.9543$ with std err $s_b= 0.1172$ . I compared this to a theoretical slope $\beta_0 = 2$, which is significantly different at the level $p = 0.00044$ (df=4). But what I ...
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### How to compensate for small errors that could greatly distort observed ratios?

Lets say for two samples, treatment and control, there are three constituent molecules each and their corresponding amounts are as follows: ...
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### T-test / ANOVA on Box-Cox transformed non-normal data

Suppose I apply a Box-Cox transformation to my data and now it looks rather like a normal distribution. I then add another dataset, transform it by Box-Cox with the same lambda and run a t-test to ...
596 views

### Transform Data to Desired Mean and Standard Deviation

I am looking for a method to transform my dataset from its current mean and standard deviation to a target mean and a target standard deviation. Basically, I want to shrink/expand the dispersion and ...
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### Questions about thresholding the data

I came across a data mining course project online. The data is of samples with 7000 features as genes. Each gene is associated with a value. Some of the values are negative. The data looks like in ...
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### Back-transforming a reflected logged variable

In order to prepare variables for multiple imputation, I did some data transformation on skewed variables. Therefore, I reflected them (largest value+1 minus variable) and took the lg10. After ...
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### Compare means - heterogeneous variance, non-normal

I would like to perform some basic means comparisons (3 conditions, balanced, n = 21 for a total of 63 observations). The main dependent variable is total task completion time, i.e., the experimental ...
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### Transformation of the datasets with negative numbers for exponential graph?

I have a simple question for data transformation for fitting my dataset to a negative exponential graph. There are negative values on my dataset which hinder fitting a negative exponential curve. How ...
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### Box-Cox transform units and scaling

Why is the Box-Cox transform defined the way it is, in particular with regards to the geometric mean? In particular, if you're paying attention to units, wouldn't you need to use ...
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### Linear regression from data that don't represent a function

I have $(x,\ y)$ pairs with a strongly suspected linear correlation. So I want to fit the "best" linear function in order to make predictions for unknown $x$'s. These pairs don't represent a function, ...
7k views

### Does it ever make sense to treat categorical data as continuous?

In answering this question on discrete and continuous data I glibly asserted that it rarely makes sense to treat categorical data as continuous. On the face of it that seems self-evident, but ...
311 views

### p-values of Mann-Whitney U test identical for raw and log-transformed data

I am new to Stats and came across this problem while running my analyses on SPSS which I cannot explain. How is it that even after transforming my data by logging it, it still has the same p-value ...
2k views

### Box-Cox like transformation for independent variables?

Is there a Box-Cox like transformation for independent variables? That is, a transformation that optimizes the $x$ variable so that the y~f(x) will make a more ...
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### Transformation to normality for random variables with different locations

I have a (potentially infinite) sequence of random variables $X_i$, with $i = 1, 2, \dots$, which have the same distribution (in terms of "shape"), but different locations. I have a sample of size ...
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### Transforming the explanatory variables

What are the considerations that we need to take into account if we need to transform just the explanatory variables (not the dependent variable). I have data on assets and liabilities and I need to ...
33 views

### Plotting variables in transformed space

Suppose $A = X_1/X_2$ and $B = X_3/X_4$. Why would one plot the data in $(\log A, \log B)$ space as opposed to $(A,B)$ space?
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### Overlapping time series: is there any better way to visualize them?

I have this time series dataset: The graph shows trend lines for 7 stock prices. They are very close and overlapping, but you will be able to get an idea that trend lines are layered (i.e. brown ...
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### Ratio data with categorical events

I have a question about treating qualitative (categorical) events within otherwise quantitative (ratio scale) data. Without going into too much detain, the experiment is on throwing. I measure the ...
49k views

### How to summarize data by group in R?

I have R data frame like this: ...
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### Plot of copula (based on data set) - R

I have to do an empirical analysis for a statistics paper. For this I want to show the differences of dependence structure for a specific data set. So I selected 2 stock prices, transformed them into ...
Let us say we have this regression $$\ln(y) = a + B_1(age) + B_2\ln(savings) + B_3\ln(income+1)$$ When carrying out the regression we obtain: \ln(y) = 0.3445 + 0.5(age) + 0.4556 x_1 + 0.55566 ...