Statistical Analysis Stack Exchange
Statistical Analysis Stack Exchange

Questions tagged [underdispersion]

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

Underdispersion is when there is less variability than there 'ought' to be in the data. For example, the variance of a set of counts could be less than the mean, whereas the variance of a Poisson should equal the mean. Underdispersion can be contrasted with overdispersion, which is a much more common phenomenon.

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What is the appropriate model for underdispersed count data?

I am trying to model count data in R that is apparently underdispersed (Dispersion Parameter ~ .40). This is probably why a glm with family = poisson or a negative binomial (glm.nb) model are not significant. When I look at the descriptives of my…
Sil
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Overdispersion and Underdispersion in Negative Binomial/Poisson Regression

I was performing a Poisson regression in SAS and found that the Pearson chi-squared value divided by the degrees of freedom was around 5, indicating significant overdispersion. So, I fit a negative binomial model with proc genmod and found the…
StatsStudent
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Does binomial distribution have the smallest possible variance among all "reasonable" distributions that can model binary elections?

Imagine an election where $n$ people make a binary choice: they vote for A or against it. The outcome is that $m$ people vote for A, and so A's result is $p=m/n$. If I want to model these elections, I can assume that each person votes for A…
amoeba
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GLM for proportional data and underdispersion

I'd like asking your help to understand a statistical issue from my data set. I ran a GLM with proportional data, using a binomial distribution. However, I've found underdispersion in my model and I don't know how to deal with that. I'm aware that a…
Mauricio
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How to deal with underdispersion with binomial data

I'm working with a pretty large dataset (n = 4,500) where 10% of my points (pixels in a GIS landscape) are 1s and the rest are 0s. The full model for my data looks something like this: model.full = glm(pond~elev+slope+landform+strmord+wcover,…
Alejandro
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Can I ignore under-dispersion in my count data?

I have under-dispersed count data. I do not want to transform them, and using a negative binomial error distribution (via glmer.nb) does not help. My results are the same regardless of the distribution I use, and agree very well with the conclusion…
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Are these data underdispersed? If so, what mechanisms may explain this?

Say someone who is well practiced (appears to have reached a performance plateau) shoots 20 free throws on 15 different days and is successful the number of times shown in the upper histogram (dat in the code). My understanding is that the…
Livid
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How to handle underdispersion in GLMM (binomial outcome variable)

I'm working on the following model in R: Generalized linear mixed model fit by maximum likelihood ['glmerMod'] Family: binomial (logit) Formula: Tooluse ~ Sex + Age + Frequency + Tool.related.skill + (1|Trial) + (1 +…
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Modelling count data with extreme underdispersion - what distribution?

Suppose we have some count data, and we want to use a model that allows for "overdispersion" or "underdispersion" in the data (i.e., higher or lower variance than the Poisson distribution). Let $X$ be our count variable and let $\phi =…
Ben
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Quasi-poisson for underdispersed data

Related to glm() in R, I saw a few post recommending modeling underdispersed data using the Conway–Maxwell–Poisson distribution, specifically with the R package CompGLM, however, I'm not sure I saw anybody confirming that the quasi-poisson cannot be…
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How different from one does a dispersion ratio have to be to be considered significant?

I am in the process of conducting zero-inflated generalised mixed effects models with Poisson distributions and have been using the testDispersion() function of the DHARMa package in R to determine if my data is significantly over/underdispersed.…
Ladybird_biologist
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Sampling from under/over-dispersed count data in R

I am currently working a some datasets with count data in R, in which the response is the number of activities of a given type that were performed in one day by a population. For each type, I build a Poisson model and test for over/underdispersion…
Gabriel LM
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Improving fit of underdispered beta regression model in glmmtmb

I have survey data where the outcome is the proportion of a research budget interviewees wished to assign to one of three different "types" of research into solutions for various issues. I am investigating how this proportion varies with the issue's…
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Zero-inflated generalized Poisson mixed effect model with glmmTMB still zero inflated

I am trying to analyze a dataset using number of flowers as response variable and the interaction between two treatment variables (categorical with 2 and 3 levels) as covariates. I also have a random effect, which represents different areas where…
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Is there a common underdispersed discrete distribution with unbounded support for general mean and variance?

I have a mean $\mu$ and a variance $\sigma^2$ with underdispersion, i.e., $\sigma^2<\mu$. Is there a standard discrete distribution with these moments and unbounded-on-the-right support, i.e., support on $\{0, 1, \dots\}$? Bonus points if it is…
Stephan Kolassa
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