The overdispersion tag has no wiki summary.
0
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1answer
44 views
how to test for overdispersion in Poisson lmer()
I have the following model:
> model1<-lmer(aph.remain~sMFS1+sAG1+sSHDI1+sbare+season+crop
+(1|landscape),family=poisson)
...and this is the summary ...
3
votes
1answer
97 views
Extra negative binomial distribution or extra binomial distribution
I doubt how to treat my outcome variable, and consequently, which regression analysis I should apply. I'm working with a count variable, namely the times a person said "I don't know" on a total of 45 ...
3
votes
2answers
51 views
Which test should I use?
I have a set of probabilities that an event will occur (yes/no). E.g. [0.87, 0.56, 0.97], and I need to know "What is that probability that at least X of these events occurs?". I've been looking into ...
1
vote
1answer
114 views
How to get dispersion parameter from a binomial mixed model?
I am modelling data with a generalized mixed model with binomial error distribution and I am concerned about overdispersion. I know that dispersion parameter can be measured as deviance/df, but for ...
0
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1answer
26 views
What is the global model?
I'm trying to calculate c-hat, the overdispersion parameter for a QAIC model set. According to Burnham and Anderson, you're supposed to calculate c-hat on the global model. Is the global model the ...
4
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1answer
1k views
How to assess overdispersion in Poisson GLMM, lmer( )
I have a GLMM with Poisson distribution and random spatial block. My experimental design is 2x2 factorial, with 4 blocks, resulting in 16 total data points. Here is the specification of the model in R ...
1
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0answers
74 views
Comparing overdispersion distributions
I am dealing with handling overdispersed count data(Poisson distributions fails to fit).
I need to compare three different mixtures (Gamma, Log-Normal and Inverse Gaussian) of Poisson rate parameter ...
0
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0answers
251 views
Overdispersion in GLMM in SPSS
I am using a generalized linear mixed model to analyze poisson and binary data. Animals were observed on several moments, so my model should account for that, which is why I am using the GLMM. I am ...
3
votes
1answer
242 views
Limits of correction for over dispersion with Poisson / binomial data
Reading many help pages, I see that a common way to correct for overdispersion is to fit models using quasibinomial or betabinomial distributions. However, I can't find help concerning how far ...
4
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1answer
110 views
Modelling both mean and dispersion of count data
I have a model of the following form:
$P(Y \mid X) = \,D(\mu,\sigma^2) ~~\text{where}$
$\mu = f(X) ~~\text{and}~~ \sigma^2=g(X)$
where $y$ is the response vector of count data, $X$ is the predictor ...
1
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0answers
70 views
Fitting a complex model of variance-vs-mean for quasi likelihood models? (in R)
I wish to deal with over dispersion of a Poisson model. Negative binomial (glm.nb), and quasi likelihood models (family=quasi in glm) do not offer a flexible enough structure of the variance-vs-mean ...
1
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0answers
267 views
Types of dispersion parameter for binomial data
For a model with a binomial proportion as response variable, which is fitted with according to a binomial distribution, a dispersion parameter $\phi$ can be calculated, which is equal to the sum of ...
4
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0answers
291 views
Very different scale parameter estimates in Poisson regression
The background: I'm analysing survival data using a Poisson model. I've splitted the data on 2 time-scales (attained age and calendar year). Attained age is modelled using flexible parametric ...
1
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0answers
47 views
Relativization and tackling an overdispersed dataset
If there is a species that is hyperabundant in a dataset and makes up 284/1638 individuals yet originated from just 1 of 10 traps. Is a quassi-poisson GLM sufficient providing residual deviance is ...
2
votes
2answers
3k views
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. ...
9
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2answers
354 views
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 ...
1
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1answer
1k views
Fitting a beta-binomial model in the case of overdispersion in R
I'm estimating some count data. I have counts for say $m=100$ individuals. Unfortunately when using the Poisson regression overdispersion occurs. So I was thinking to fit a negbin model. But this is ...
0
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2answers
352 views
Dispersionparameter of negbin distribution
Can anybody show me, why the Dispersionparameter of the negbin distribution is taken to be one? In the Poisson case you can show that E(y)/var(y)=$\mu/$\mu=1 which is called Equidispersion. But how ...
7
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3answers
956 views
How to model zero inflated, over dispersed poisson time series?
I am trying to model weekly disease counts in 25 different regions within 1 country over a ten year period as influenced by temperature. The data is zero inflated and over dispersed.
I am most ...
13
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4answers
828 views
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 ...
15
votes
4answers
3k views
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 ...
7
votes
2answers
995 views
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 ...
