# Questions tagged [negative-binomial-distribution]

A discrete, univariate distribution modelling the number of ${\rm Bernoulli}(p)$ trial successes until a specified number of failures occur.

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### Zero Inflated Negative Binomial not producing standard errors - R

I've recently learned about using ZI-Negative Binomial in R, but I haven't been able to figure out why my model results are not calculating a standard error. ...
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### How can I improve unbalanced error residuals in mixed-model negative binomial regression?

I wish to determine the factors that influence seedling density. The density data are highly right-skewed with mostly zeros; values vary from 0-35. Potential influencing factors measured were the use ...
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### Negative binomial assumptions and errors

I'm conducting a negative binomial regression in SPSS using the GLM menu and I'm receiving the following error message: Warnings: The Hessian matrix is singular. Some convergence criteria are not ...
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### How to calculate the percentage deviance explained wiith glm.nb?

I’ve observed that when I fit a Negative Binomial regression with glm.nb, the null deviance I get from the model differs from the deviance of the null model. I think this is because both models ...
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### how to compute marginal effects of predictors in NBSTRAT (truncated & endogenously stratified negative binomial) model? (Stata)

I'm using STATA 16.0 to develop recreational demand function via using NBSTRAT model. I have several factor and continuous variables that force me to use "xi:" prefix in the model syntax ...
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### How can I interpolate within a negative binomial distribution?

I have information about a negative binomial distribution at the 10%, 50%, and 90% quantiles. I want to be able to interpolate to know what the probability of a certain count is within this ...
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### Is there a way to supress p-values in tbl_regression function in R? [closed]

I want to make tables including exponentiated parameter coefficients with CIs, but not with p-values. Right now i am using : ...
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### Likelihood loss function for finite support probability distribution in Neural Networks

I have managed to reproduce solution from this article and made it work for my dataset. Instead of making a Neural Network output a scalar (regression), we make it output two parameters of a ...
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### Why p-values are inconsistent when applying model on subsetted data versus using interaction terms

I have the following negative binomial GLM, where "group" is either Control or Experimental and "count" shows the number of times patient came to hospital. ...
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### Why can negative binomial regression be used to model event rate/count data

It seems negative binomial regression can be used interchangeably with Poisson regression to model event rate? but I don't understand how it works. Poisson distribution is for count data. Poisson ...
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### How to account for temporal autocorrelation in a hierarchical generalized additive model (HGAM/GAMM) with a negative binomial distribution?

I am using a harvest data set (count data) that I am trying to infer population abundance from. This data set contains annual harvest estimates from 20 Zones of varying areas, spanning 34 years. While ...
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### GLMM appropriate for constant covariates/ baseline score? Or Ancova?

I was wondering whether my data is appropriate to fit a glmm (with r package lme4) So, I measured a questionnaire two times (q1 and q2). Also, I have variables ...
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### Intuition for reasoning between Quasi-poisson and Negative Binomial regression

I am aware of the several similar questions existing here (like this, this or this), but my question is slightly different and remains after going through most of those posts. Specifically, my ...
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### Applying count models with rate responses

How do you apply count models to data which is count in nature, but a rate in reality? In such cases, r can handle this to a certain extent, depending on the model, but what is the correct way to ...
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### quasi-poisson / Neg.Bin / Chi-square for analysing annual count data?

I'm interested in looking at annual trends. The numbers represent the total number of a particular animal species that have been counted in that year. We see a decreasing trend, and I would like to ...
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### Excessive amount of zeros - percentage data

I am totally new to using glm-function. I have tried to model my data with lmer-function but the excessive amount of zeros skew the residuals heavily (cubic root transformation helps some tho). The ...
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### Poisson Approximation to Negative Binomial

While r tends to infinity, p tends to 1, and (1-p)r tends to lambda, we obtain Poisson distribution from Negative Binomial Distribution. X in Neg Binom(r,p) is the number of failures; x=0,1,2,3,4.... ...
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### What is the difference between conditional and unconditional fixed effects?

What is the difference between unconditional and conditional (fixed effects negative binomial) regression models? A similar question was asked for quantile regression here: What is the difference ...
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### Analyze count data errors of commissions - is my model fine?

Is my model doing a good job here? I have errors of commission in a SART-task as a dependent variable and stress index and its interaction with a group (2 groups) as an independent variable. The ...
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### Truncated NB? Or go with linear?

I am not here to ask about which R package to use, etc. I am here about model selection. The question I am trying to analyze is - What is the association between Indicator 1 and age, sex, and group? ...
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### How to check for heterogeneity over time and location for rate data

I have data that consists of different locations, with repeated observations over time, of counts (and a denominator to make a rate). eg ...