Questions tagged [lognormal-distribution]
A lognormal distribution is the distribution of a random variable whose logarithm has a normal distribution.
702 questions
1 vote
1 answer
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Should I log-transform individual timepoint measurements or the absolute change score when my outcome is volume (cm³)?
I have a longitudinal dataset where my outcome is white matter hyperintensity (WMH) volume measured in cubic centimeters (cm³) from brain MRI, collected at baseline and follow-up for each participant. ...
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6 votes
1 answer
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How should I interpret the dispersion parameter in my glmmTMB lognormal GLMM?
I have run a lognormal GLMM using the glmmTMB package, and I could use some help understanding the dispersion parameter. It is very large (2210), but there are no model convergence issues and no ...
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0 votes
2 answers
388 views
Log Transformation of variables
I am working with panel data to estimate spatial spillover effects. 3 of my variables, which are in percentage form, show skewness more than 1. I am not sure whether I should transform them using log ...
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1 vote
1 answer
137 views
Regression model residuals issue
I have a dataset for trees geometrical characteristics. Simply, I want to predict the root width for example from these predictors above the ground. At the end of the day I want to a simple model or ...
0 votes
0 answers
30 views
Why is the ones trick making my hurdle model crash in jags?
I'm running a hurdle model in JAGS but if randomly crashes for reasons I cannot determine. The model describes the presence absence of a species and, when the species is present, its biomass. It uses ...
8 votes
4 answers
1k views
Should I transform my data before or after removing outliers? (Highly skewed cortisol example)
I am analyzing cortisol data collected over multiple days, with three samples per day (Cortisol_1, Cortisol_2, Cortisol_3). My data are extremely skewed: Skewness of Cortisol_1: 26.3 Skewness of ...
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0 votes
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37 views
Package for fitting a mixture of Gammas (or LogNormals) with location/shift as a free parameter
I have a sample data that I'd like to characterize with a mixture of skewed distributions – in this case, mixture of Gammas (although I am open to LogNormals as well if Gammas is not an option.) ...
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0 votes
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Sampling distribution of estimated and individual glomerular filtration rate
I would like to determine correlation betweeen eGFR/GFRi and renal clearance of a drug.Can the estimated glomerular filtration rate (eGFR) and individual glomerular rate (GFRi=eGFR adjusted for body ...
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8 votes
2 answers
512 views
Correct interpretation of an estimate which is outside its confidence limits
I have computed a geometric mean ratio (variable=area under plasma concentration curve) of two groups (males/females) as 0.9338682 and its 90% confidence interval as 0.9684333 to 1.184019. Clearly, ...
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1 vote
1 answer
177 views
Confidence interval of the ratio of two geometric means of lognormal data
How can I compute the 90% confidence interval of the geometric mean ratio of two unequal groups given the group sizes, geometric means and geometric standard deviations of the two groups? I have tried ...
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0 votes
0 answers
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Hurdle modelling of heavy tails for continuous variables
In a standard hurdle model[ [wikipedia]][1], the decision to participate would be associated to some strictly positive outcomes (eg positive count if Poisson) and non-participation would necessarily ...
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1 vote
0 answers
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Determine sample size based on a pilot to estimate the variability of ratios within a given level [closed]
After thinking back and forth for a long time, I just can't get any further with a problem. Basically, the question is how representative a number of samples is for a population. The word “...
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1 vote
0 answers
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Modifying Gaussian Processes and/or using transformations for dealing with positive-only output values? [closed]
I've been reading into different Gaussian processes recently to better fit some data that I'm working with. My data clearly does not follow a multivariate Gaussian as required for a standard exact ...
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0 votes
2 answers
111 views
Issues with Survival Regression in R: Handling Non-Censored Data and Model Convergence Problems
I am working on survival regression in R using a dataset where individuals are tracked from birth to death. Their health status is classified as either Tumoral or Healthy, under two dietary regimes (...
1 vote
1 answer
72 views
Comparing log-normal distributions, metric?
Naively, one might compare two normal distributions based on their mean or median to determine which one is more appropriate. However, if I know that a metric follows a log-normal distribution, such ...
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