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).
97
questions
1
vote
1answer
14 views
Back-transformations
I have been having trouble grasping the idea of back-transforming data in R. Lets assume that I would like to perform an ANOVA on transformed data. I transform the response variable and all the ...
0
votes
1answer
42 views
Standardize-back the Standard deviation
I run an lmer model using standardized data like scale(y) ~ 1 + (1|categorical)
Now, I have a standard deviation for the random effect in normalized world but I ...
0
votes
0answers
6 views
Do I need to backtransform the estimates of a model produced with the mhurdle package using box-cox normal distribution?
I am currently running a double hurdle model with the R command "mhurdle". My data is not normally distributed and I am using the box cox normal distribution on because that yields the ...
0
votes
0answers
13 views
Can we transform back calendar adjusted forecast?
I've monthly data, I adjusted it for monthdays and conducted a forecast. After that can I adjust it back and compare it with untransformed time serie?
0
votes
0answers
20 views
Back-transformation of coefficients in a log-log model, and a model with a boxcox transformed y
There's a number of posts out there on back-transformations but none that I've been able to use to answer this problem, internet searches are returning surprisingly little on the issue of back-...
0
votes
0answers
12 views
Interpreting differences in log-transformed data when constant has been added first
I have performed an ANOVA on some log-transformed data. I had planned to transform the mean differences in the log-transformed data back to the original scale and interpret them as ratios of the ...
1
vote
0answers
45 views
Pairwise contrasts for logistic regression in emmeans, back-transform or not?
I ran a mixed effects logistic regression in R (glmer). The model identified a significant three-way interaction that I am interested in decomposing using post-hoc multiple comparison in emmeans. In ...
0
votes
0answers
20 views
What is the back-transformation of Log((Max Y + 1) - Y)?
I have performed a linear mixed model regression with the transformation on the outcome variable, Y, Log((Max Y + 1) - Y). This gives normally distributed residuals when simpler transformations did ...
1
vote
0answers
25 views
predicting waste per capita: is a Gaussian model correct?
I am trying to predict the daily amount of waste per person produced in the fishery sector. We surveyed fishing boats at the end of their fishing trip and the variables I have are duration of trip (...
1
vote
1answer
107 views
XGboost Regression Log Transform Target
I'm training a XGBoost Regressor to predict price which has a highly right skewed distribution. (all prices are positive)
I took log transformation on the target thinking it would help to 1) stable ...
0
votes
0answers
14 views
Transformation of Beta distribution prior parameters for group testing analysis
As described here Optimization of pool size and number of tests for prevalence estimation via group testing I'm trying to estimate the prevalence of a lab test in a population (PCR for COVID-19) ...
0
votes
0answers
18 views
Back-transforming coefficients of glmer model fit using rescaled independent variables for prediction & plotting
I've fit a model using the glmer function from the lme4 package. Because my predictor variables are on very different scales, I ...
0
votes
0answers
58 views
Unmarked OccuMulti function
I have a question about the occuMulti function in the package “unmarked”.
I have fitted the following model for a two-species interaction between puma and peccary:
...
1
vote
0answers
49 views
Back-transforming forecast points and error bounds from a VAR model applied to alr-transformed compositional time series
The data
I have a k=3 compositional time series from which I am trying to forecast future values.
The series is compositional in that at each time ...
0
votes
0answers
21 views
Transforming AR1 Parameter back to “Non-Stationary” Times Series
I'm kind of stuck on this so any help would be hugely appreciated. My math 'skills' have so far failed me.
I have a time series that I am trying to fit into an AR(1) model. Which is expressed as :
$...
1
vote
0answers
45 views
How do I back-transfrom my estimates (and confidence intervals) from log10 variables (both independent and dependent) in linear model
I ran linear models for a bunch of variables in R. Both variables are log10 transformed (dependent and independent). I already took a look in some online documents and videos about this but i guess I'...
0
votes
0answers
54 views
What is better for skewed data, transform it with Box-Box or fit a GLM with appropriate link and distribution?
In the scientific community I can distinguish two "tribes": older statisticians prefer transformations, especially via Box-Cox, while younger statisticians prefer GLM. I was told, that:
transforming ...
1
vote
1answer
104 views
How to get the actual mean absolute error in cross validation after transforming the target variable y?
For a target variable y, it is transformed using np.log1p. Then a random forest regression model is trained using the ...
17
votes
1answer
662 views
Predicting y from log y as the dependent variable
In the book Introductory Econometrics by Wooldridge the chapter, which deals with predicting values of $\hat{y}$ (chapter 6.4 in the 5th edition) states the following:
If the estimated model is: ...
0
votes
1answer
46 views
Which one is correct presentation for descriptive statistic of a transformed variable between retransformed mean (estimated SD), and median (qurtiles)
If a collected variable has a skewed distribution toward one side and transformed for statistical analysis, which one is better for descriptive statistics presentation between re-transformed mean and ...
0
votes
0answers
27 views
Orthogonal backtransformation for plotting marginal effects
I have the results of a linear model within which I used orthogonal polynomials. To aid interpretation, I am trying to plot the marginal effects of the linear + quadratic term for each independent ...
3
votes
1answer
136 views
When is performing back-transformation of inferences on transformed variables Ok, and when is it not Ok?
Caveat: This question may be a tad rambly, and I welcome comments with specific directions for me to improve it.
During a too brief exchange with the worthy @NickCox I got to thinking about ...
1
vote
0answers
92 views
How to plot estimate + raw data of a Bayesian zero inflated poisson?
GENERAL QUESTION:
How to back-transform estimates from a zero-inflated poisson to obtain the original scale in R?
(I tried exponential like for poisson but the results are wrong)
DETAILED ...
0
votes
0answers
68 views
Why are the confidence intervals so large for the difference of differences?
I have run a generalized linear mixed effects model with the glmmTMB package to determine if there is an interaction between two categorical predictors, treatment and location, in predicting the ...
0
votes
0answers
113 views
Back transforming the intercept of double log normal distribution
I apologise if this is a duplicate, i couldn't find a thread that seem to be talking about the same thing.
I have a dataset with a bunch of duration of varying lengths in seconds, i log-transformed ...
0
votes
0answers
187 views
Back-Transformation for Ln(X+1) of zero rich data
I have seen and read several similar questions, but mine pertains specifically to zero rich data.
I will be back transforming my data based on a first order Taylor series approximation. As outlined ...
2
votes
2answers
172 views
How to back transform a folded root?
I have some data where the response variable is a proportion, and I am experimenting with transformation using Tukey's family of folded powers, $f(p) = p^\lambda - (1 - p)^\lambda$, with values of $\...
0
votes
1answer
33 views
Log transformed data
When you log transform data what is being tested on the original scale of the data? And why can we use our log transformed data to answer our scientific question?
We are looking at data comparing ...
0
votes
1answer
147 views
Transforming non-normal to normal distribution and back-transform
I would like to transform non-normal distribution to normal distribution, and back-transform to its original state (or at least close to the original state).
From this article, I've read that you can ...
1
vote
1answer
454 views
How to back-transform negative Beta coefficients of linear regression after log transformation?
For a linear regression model, I have had to perform a natural log transformation of a response variable due to non-normal distribution in R. I am in the process of back-transforming the coefficients, ...
0
votes
1answer
100 views
slope in a log-transformation
Given y(x) = A*exp(x+c). I'm converting the y-axis into a log-scale. Then I calculate the slope at a certain point.
Am I'm allowed to re-transform this value dy(x)/dx? Hence: exp(dy(x)/dx)?
2
votes
0answers
63 views
How to recalculate Confidence interval after logarithmic and square transformations?
I'm performing test on one variance and in order to asses normality of X, I've transformed data with first natural logarithm transformation,then square transformation and calculated confidence ...
2
votes
1answer
2k views
Reporting glmer.nb Results
I'm running a mixed negative binomial GLM that looks like this:
Niche2 <- glmer.nb(log_density ~ height * factor(Year) + (1 | Grouping), data = NicheData2)
...
2
votes
0answers
197 views
Interpreting forecast predictions of log transformed data
Using the forecast function in R, I make a 1-step prediction for a log-transformed data set Y, ( Y = log(X) ). This prediction gives me a mean and a 95% prediction interval.
How valid is this ...
2
votes
2answers
2k views
Linear mixed effect model interpretation with log transformed dependent variable
I have a dataset in which the response variable is non normal, but on log transforming, it follows the normal distribution. I constructed a mixed effect model using lme4::lmer() as below (multiple ...
0
votes
0answers
69 views
Back transforming in t test using sqrt [duplicate]
I have one sample with values of sugar intake pre and post intervention. I transformed the values for t test as the change from pre to post was negatively skewed but now I dont know how to report the ...
5
votes
1answer
6k views
How to back-transform a log transformed regression model in R with bias correction
I have created a model to predict the number of people with a certain characteristic (Y) based on predictor variables $X_1$, $X_2$, $X_3$, $X_4$. The model is a multiple linear regression and both the ...
1
vote
0answers
786 views
Smearing retransformation in r [duplicate]
I ran a regression model with the Y variable (length of stay of patients in days) log10 transformed. I would like to compare the fit of the log10 transformed model with a similar regression where the ...
2
votes
1answer
781 views
Backtransforming log(x+1) transformed SE
I am back-transforming y=log(x+1) data that represent individuals/m^2 of area. Data are in the form of X ± SE. I back-transformed the means, but I am wondering if it's possible to directly back-...
4
votes
1answer
614 views
Standard errors in R, package emmeans
I am fitting a multinomial logit model in R by using the multinom() function in the nnet package. I would like to retreive the proportions in each class for the two ...
0
votes
0answers
74 views
Interpret Quadratic Regression with Asinh transformation
I have a regression equation that uses covariates of the following form
asinh(y) = b0 + b1 asinh(x) + b2 (asinh(x))^2 + error
and am wondering how to intepret the ...
2
votes
1answer
164 views
How to convert estimated precision to variance?
I have a simple model in INLA (the regressor is a single model=iid term), which reports the precision of the hyperparameter. How ...
0
votes
0answers
359 views
Box-Cox Transformation on Single Variable and Interpretation of the Transformed Variable's Mean and Standard Deviation
I'm revisiting the Box-Cox transformation in one of my stats books, and I started playing around with the SAS macro %BCTRANS2 (Source: http://support.sas.com/resources/papers/proceedings12/430-2012....
0
votes
0answers
43 views
95% CI interpretation on transformed data using (abs(x-mean(x)))
I have a problem for which no search has provided an answer.
I am using lm() to build a model which I tested to ensure it met all assumptions using the following
<...
3
votes
1answer
468 views
back transformation of log means and log standard deviations
I have a set of values reported as the 'log mean'. I know from elsewhere in the text that it is the natural log that is being referred to. I'm trying to ascertain if there is a way I can derive the ...
1
vote
1answer
2k views
How to calculate the standard deviation of a sample and its 95% CI if I know the variance and its 95% CI?
I apologize if my question is extremely simple, but you know my name.
I have only the variance of a sample and its 95% confidence intervals, nothing more, nothing less.
Please correct me if I am ...
0
votes
1answer
4k views
Regression RMSE when dependent variable is log transformed
I want to predict the duration a trip would take. For this I transformed my dependent variable (trip time in sec) to log transformed.
When I do regression on this variable with some other features,
...
0
votes
1answer
125 views
Multiple linear regression back-transformations
My Multiple Linear Regression equation is (I had log-transformed swim beach E. coli and canal E. coli for the MLR since the data were not normal):
(LN)Swim Beach E. coli = 2.4 + 0.43 * Reservoir ...
2
votes
0answers
123 views
How to compute confidence intervals for a scaled reciprocal normal statistic
I have the following statistic of which I want to compute confidence intervals:
\begin{equation}
Z = \frac{(X-Y)^{-1}}{\mathbb{PVE}[(X-Y)^{-1}]},
\end{equation}
where
\begin{align}
X &\sim\mathcal{...
2
votes
1answer
2k views
Back transform mixed-effects model's regression coefficients for fixed-effects from log to original scale
I am running a mixed-effects model with the lme4 package. The model specifications are: ...
