Linked Questions
22 questions linked to/from When to use gamma GLMs?
19
votes
1
answer
30k
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Log-linked Gamma GLM vs log-linked Gaussian GLM vs log-transformed LM
From my results, it appears that GLM Gamma meets most assumptions, but is it a worthwhile improvement over the log-transformed LM? Most literature I've found deals with Poisson or Binomial GLMs. I ...
- 978
5
votes
1
answer
14k
views
What to do with GLM (Gamma) when residuals are not normally distributed?
Until now I have only done very basic/simple simple stats, but now I got stuck in all the literature/tips/forums ... It's about the following problem:
I have the following data:
...
- 153
8
votes
1
answer
31k
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GLM Gaussian vs GLM Binomial vs log-link GLM Gaussian
I am trying to do a study of deaths due to malaria in order to find the best way to predict how dangerous this disease is.
I don't have a strong background in statistics, I am an auto-learner ...
- 1,157
28
votes
1
answer
11k
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When to use Poisson vs. geometric vs. negative binomial GLMs for count data?
I'm trying to layout for myself when it's appropriate to use which regression type (geometric, Poisson, negative binomial) with count data, within the GLM framework (only 3 of the 8 GLM distributions ...
- 1,133
10
votes
1
answer
9k
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Confusion related to which transformation to use
I have this confusion about which transformation to use in my data. The histogram of my original data looks like this
Now I have seen at most of the places to take log transformation in case the ...
- 6,847
4
votes
3
answers
11k
views
What are the assumptions of a Gamma GLM or GLMM for hypothesis testing?
What are the assumptions when doing hypothesis testing using a Gamma GLM or GLMM? Are the residuals suppose to be normally distributed and is heteroscedasticity a concern like the Gaussian (normal) ...
- 412
5
votes
2
answers
788
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What is special about the Poisson/Binomial distributions such that they have special regression estimation techniques?
You can use maximum likelihood estimation to estimate the regression parameters for a random variable with Poisson or Binomial distributions, but I haven't heard of a chi-squared regression or a Gamma ...
- 173
5
votes
2
answers
2k
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Log-linear and GLM (Poisson) regression
I am afraid I am asking a stupid question... but...
I would like to study the spending (my outcome variable) of a company by department, number of staff, activity, etc. I have collected my data and ...
- 99
5
votes
1
answer
7k
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Strictly positive response in regression: what should my "default" model be?
For unbounded continuous responses, Gaussian errors are the analyst's default model for many reasons, one of them being that their ML estimate coincides with the OLS estimate that has many desirable ...
- 12.8k
1
vote
2
answers
6k
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generalized linear model with log link using log transformed fixed/random effects?
I am modelling a longitudinal dataset consisting of a continuous response variable (mutation count) with a binary predictor (medical history, ie previous medications) while accounting for time and ...
- 163
3
votes
1
answer
3k
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Prediction of continuous, strictly positive, right-skewed outcome
I am trying to predict a strictly positive, continuous, right-skewed variable (purchase value) given a set of categorical attributes.
The current popular options include:
1) log-transform the variable ...
- 701
1
vote
2
answers
1k
views
A workaround for using linear models (rather than Tobit) with censored data?
I have a left censored dependent variable where many of the observations have a value of zero. The data is clustered (multiple measurements over time for each person). I initially decided to use a ...
- 11
1
vote
1
answer
2k
views
Should I use Binomial, Poisson or Gamma distributions? With or without a log link?
I want to run a GLM to answer a few questions about differences in diet between sex and calendar year.
Questions:
Does frequency of occurrence (FO) of pieces eaten differ between sex or year?
Does ...
- 145
0
votes
1
answer
1k
views
Nested mixed effects anova with lmer
I want to analyze some data from an experimental study with 3 factors:
treatN= nutrient manipulation 2levels N=nutrients added, A=ambient (fixed effect)
treatH= herbivory manipulation 3 levels C=...
2
votes
1
answer
775
views
Improving a model for a positively skewed continuous data (no zeros)
I have a positively skewed continuous data (no zeros), representing transactions by amount.
Variables age and income were ...
- 259