Questions tagged [back-transformation]
Back transformation refers to efforts to reverse the effects of a transformation of one or more variables. Usually, the transformation has been done to meet assumptions of a model, but interest is in the original variable(s).
138
questions
3
votes
1
answer
44
views
What should I back transform beta coefficients when my dependent variable is fractionally exponentiated in R
I have this mixed effects regression model. To create a normal distribution in continuous scale dependent variable, I fractionally exponentiated it:
...
3
votes
1
answer
186
views
Back Transforming log-log Model for Prediction
I have a model that is log-log and I would like to make raw predictions of $Y$ with it:
$\ln(Y) = B_0 + B_1\ln(X)$
All answers and articles I have found concerning back transforming for prediction ...
- 73
0
votes
0
answers
11
views
Variance decomposition with Tweedie distribution – back transform necessary?
We are running a hierarchical random intercept model with a Tweedie distributed dependent variable (see below) and three levels of hierarchy. Our aim is to estimate how much of the total variance (in ...
2
votes
2
answers
68
views
Back Transformation of Predicted Y from Log 10 Transformed Model Data
I am using a General Linear Model for Analysis in Minitab.
I have two questions.
I had two responses variables which I transformed using Log10 as there was evidence from the residual plots of some ...
- 31
1
vote
0
answers
28
views
Equivalent GLM's for common stabilising transformations
I'm familiar with applying a log-transform to a skewed outcome variable to improve model fit, but I've not thought further to link stabilising transforms to GLM's in general. Reading around it seems ...
- 771
2
votes
1
answer
57
views
Backtransforming a probabilistic forecast?
Let's say that we have a probabilistic forecast for the future percentage return of an asset in the form of a probability density, $\hat{R}_{t+1}$.
If our initial goal was to create a probabilistic ...
- 451
0
votes
0
answers
11
views
How to back transform a folded power transformation?
I work with a dependent variable with values from 0 to 1 and because I have a lot of 0 and 1 in this variable, i'm doing a folded power transformation with the following formular: y = x^0.5 - (1-x)^0....
- 1
0
votes
0
answers
21
views
Can principal components changed by a normalization method be used to construct original data shape with SVD
I'm planning to use an algorithm called Harmony, designed for data normalization, particularly in the context of single cell data analysis. Harmony operates by taking principal components (PCs) as ...
- 133
1
vote
1
answer
74
views
Confidence Intervals around Backtransformed Log-linear Regression
Suppose we are interested in the percentage effect of a binary $D \in \{0,1\}$ on an outcome $Y \in \mathbb{R}$, which might motivate a simple regression of the form:
$$ \log Y = \beta_0 + \beta_1 D + ...
- 396
0
votes
1
answer
34
views
Interpreation - Log tranformed dependant variable and model with square term of predictor (inverted U)
I am estimating a model of the following form:
log(y) = b1 x + b2 x^2 + b3 log(z1) + b4 z2
This is an econometric model with a focus on the impact of ...
- 11
0
votes
0
answers
15
views
Should I back-transform estimate and 95%CI after a survival analysis with log-normal distribution?
I need to run a survival analysis on my data. Based on the AIC, the lognormal distribution is the most suited one. Can I report the estimates and 95% CI as they are, or do they need back-...
1
vote
1
answer
272
views
Backtransform variables in ggeffects (logistic regression)
I am running a logistic regression. Two variables are transformed for linearity with the logit of the outcome.
...
- 33
0
votes
1
answer
125
views
Interpreting linear mixed effect model results with log transformed dependent variable and log transformed predictor w/ normal predictors as well
I have a linear mixed effect model that I built using longitudinal country level data to help me predict TB incidence based on country level diabetes prevalence, HIV incidence, prevalence of ...
- 11
0
votes
1
answer
27
views
Prediction Interval for back-calculation when observation has variance
Given an existing regression curve, how do I properly account for the known variance of the dependent variable when back-calculating for the (nominally) independent variable? If I had an observation $...
- 21
0
votes
0
answers
269
views
regression question: backtransforming MAPE for log(y)
I'm fitting a linear regression between two variables and to reduce the problem of heteroskedasticity I have log-transformed the outcome variable y.
However, this makes it difficult for me, a non ...
