# 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.

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### Validity of AIC When Comparing Models with Varying Dispersion Parameters

I'm currently making a binomial model with a logit link, which is parameterised as a quasibinomial since I'm allowing it to calculate the dispersion parameter. I was wondering, since changes to the ...
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### How much dispersion is too much for quasipoisson regression?

Quasipoisson regression goes beyond standard poisson regression in taking into account overdispersion (whereby the dependent variable's variance is much greater than its mean). This is explained at ...
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### Does changing model due to overdispersion/underdispersion results in forking?

This is related to the post How much do we know about p-hacking "in the wild"?. The post does not clearly delineate the boundary between forking or not forking to me. Suppose I have a count ...
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### What is an alternative to Chi-Square for observed vs. expected variance suitable for repeated measures?

I want to test for individual-level side preference of a behaviour during an experiment, and found a way to do this using a chi-square test that uses the number of right (or left) turns out of the ten ...
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### How do you test if the average of a population is the same as the variance of the same population?

What can be a statistical test to find out if a population has the mean equal to its own variance? I.e. Mean(X)=Var(X)? I am interested in it because Poisson regression makes the assumption that the ...
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### What better I use for Negative Binomial Regression with library(MASS) glm(family=negative.binomial) or glm.nb?

Hay, im a newbie and still need more learn. I have several question, I'm trying to create a negative binomial regression model using the R and library(MASS). But i'm still confusing what sould I use ...
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### How to develop a negative binomial model where the overdispersion parameter varies as a function of one of the independent variables/covariates?

I am trying to develop a negative binomial model where the dependent variable is crash count, and the independent variables are traffic count and roadway length. Currently, with the below code, I get ...
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### Are overdispersion and underdispersion in a binomial logistic regression model an issue if the model is not being used to make predictions?

If a binomial logistic regression model is being used strictly to identify variables that have an impact on the dependent variable but is not being used to make predictions, are underdispersion and ...
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### When does a group specific dispersion parameter for the negative binomial distribution make sense?

If you have overdispersed observed abundance of multiple species including zero inflation the negative binomial distribution seems to be a reasonable choice. But if some species occur much more ...
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### Residuals of GAM models not improving with poisson or ziplss, but better with negative binomial (help with high values)

I am running GAM models on species counts with lots of zeros and high values or high counts. Residuals under poisson family have a s-like curve on qq line with models not predicting lower and higher ...
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### Meaning of "Overdispersion" in Statistics

I am trying to understand what "overdispersion" means in statistics. Based on the Wikipedia page, "overdispersion" is defined as follows : "In statistics, overdispersion is ...
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### Is there any R packages allow direct MLE estimation of dispersion in negative binomial distribution?

Using the built-in function, I can get ...
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### What does the dispersion parameter means in negative binomial regression?

I am completely new to the topic of negative binomial regression and am unsure about what the output of my regression exactly means. Before I decided to use the negative binomial regression, i did ...
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### Why fitting a Poisson GLM in an over dispersed dataset underestimate the standard error of the regression parameter?

It is claimed by many authors that if we fit the GLM Poisson model to an over dispersed dataset of count data, the standard error of the estimated coefficients will be under-estimated. Could you ...
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### Dealing with singularity and overdispersion in GLMM?

I'm running a GLMM through the lme4 package in R to detect differences in time spent feeding (response) before and after birth (my 2 categories in the variable inf_cat). I started with a Poisson GLMM, ...
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### How do I deal with ties when using rank-based normalizing transforms, e.g. Blom?

I would like to transform heavily skewed data with range (-Inf, Inf) and heavily zero-inflated into a form suitable for using GLMs for significance testing. Zero-inflation precludes the effective use ...
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### For overdispered data, should the correlation matrix exclude zero?

I have 4 species and their distributions are overdispersed in space (i.e. lots of zeros). I calculated a Pearson correlation matrix and there is a lot of cluster around the 0s and 1s. Should I ...
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### Modelling overdispersed rate data using a negative-binomial distribution

A quick overview of the analysis I'm wanting to do: I am wanting to analyze the relationship between habitat factors and the capture of my research species over a network of traps, in order to be able ...