Statistical Analysis Stack Exchange
Statistical Analysis Stack Exchange

Questions tagged [overdispersion]

Overdispersion is when there is greater variability than there 'ought' to be in the data. Eg, the variance of counts is often greater than the mean, whereas the variance of a Poisson should equal the mean.

Overdispersion is when there is greater variability than there 'ought' to be in the data. For example, the variance of a set of counts is often greater than the mean, whereas the variance of a Poisson should equal the mean.

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Is there a test to determine whether GLM overdispersion is significant?

I'm creating Poisson GLMs in R. To check for overdispersion I'm looking at the ratio of residual deviance to degrees of freedom provided by summary(model.name). Is there a cutoff value or test for this ratio to be considered "significant?" I know…
kto
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What is quasi-binomial distribution (in the context of GLM)?

I'm hoping someone can provide an intuitive overview of what quasibinomial distribution is and what it does. I'm particularly interested in these points: How quasibinomial differs to the binomial distribution. When the response variable is a…
luciano
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How do I fit a multilevel model for over-dispersed poisson outcomes?

I want to fit a multilevel GLMM with a Poisson distribution (with over-dispersion) using R. At the moment I am using lme4 but I noticed that recently the quasipoisson family was removed. I've seen elsewhere that you can model additive…
George Michaelides
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When someone says residual deviance/df should ~ 1 for a Poisson model, how approximate is approximate?

I've often seen the advice for checking whether or not a Poisson model fit is over-dispersed involving dividing the residual deviance by the degrees of freedom. The resulting ratio should be "approximately 1". The question is what range are we…
Fomite
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Poisson or quasi poisson in a regression with count data and overdispersion?

I have count data (demand/offer analysis with counting number of customers, depending on - possibly - many factors). I tried a linear regression with normal errors, but my QQ-plot is not really good. I tried a log transformation of the answer: once…
Antonin
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Are over-dispersion tests in GLMs actually *useful*?

The phenomenon of 'over-dispersion' in a GLM arises whenever we use a model that restricts the variance of the response variable, and the data exhibits greater variance than the model restriction allows. This occurs commonly when modelling count…
Ben
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Modelling a Poisson distribution with overdispersion

I have a data set that I'd expect to follow a Poisson distribution, but it is overdispersed by about 3-fold. At the present, I'm modelling this overdispersion using something like the following code in R. ## assuming a median value of 1500 med =…
chrisamiller
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Overdispersion in logistic regression

I'm trying to get a handle on the concept of overdispersion in logistic regression. I've read that overdispersion is when observed variance of a response variable is greater than would be expected from the binomial distribution. But if a binomial…
luciano
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Strategy for deciding appropriate model for count data

What is the appropriate strategy for deciding which model to use with count data? I have count data that i need to model as a multilevel model and it was recommended to me (on this site) that the best way to do so this is through bugs or MCMCglmm.…
George Michaelides
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How to deal with overdispersion in Poisson regression: quasi-likelihood, negative binomial GLM, or subject-level random effect?

I've come across three proposals to deal with overdispersion in a Poisson response variable and an all fixed-effects starting model: Use a quasi model; Use negative binomial GLM; Use a mixed model with a subject-level random effect. But which to…
Bryan
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Identical coefficients estimated in Poisson vs Quasi-Poisson model

In modeling claim count data in an insurance environment, I began with Poisson but then noticed overdispersion. A Quasi-Poisson better modeled the greater mean-variance relationship than the basic Poisson, but I noticed that the coefficients were…
Frank H.
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How to test for overdispersion in Poisson GLMM with lmer() in R?

I have the following model: > model1<-lmer(aph.remain~sMFS1+sAG1+sSHDI1+sbare+season+crop +(1|landscape),family=poisson) ...and this is the summary output. > summary(model1) Generalized linear mixed model fit by the Laplace approximation…
susie
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Parametric modelling of variance of count data

I am looking to model some data, but I am not sure what type of model I can use. I have count data, and I want a model that will give parametric estimates of both the mean and the variance of the data. That is, I have various predictive factors…
Brian Diggs
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Overdispersion and modeling alternatives in Poisson random effect models with offsets

I have run into a number of practical questions when modeling count data from experimental research using a within-subject experiment. I briefly describe the experiment, data, and what I have done so far, followed by my questions. Four different…
tomka
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How does glmnet handle overdispersion?

I have a question about how to model text over count data, in particular how could I use the lasso technique to reduce features. Say I have N online articles and the count of pageviews for each article. I've extracted 1-grams and 2-grams for each…
Sonya S.
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