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

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23 views

Alternatives to Chi-Squared for Single Categorical Outcome and Single Categorical Predictor w/counts for factors [R]

I am from an applied background, where X2 and G-tests are the default ways to analyze count data (default as in, until today, I had no idea there were other ways, as I was only taught these methods). ...
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30 views

The use of the negative binomial dispersion parameter in model selection…?

I'm doing model selection, analysing the effect of a number of variables on the number of shoots browsed by deer, using the number of shoots available as an offset variable. My data distribution is ...
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1answer
14 views

Commonality analysis in negative binomial regression?

I am new to negative binomial regression and am using Generalized Linear Models in SPSS to analyze some highly skewed count data (it is not zero inflated and the variance is much higher than the mean ...
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1answer
94 views

Why is the Quasipoisson in glm not treated as a special case of Negative Binomial?

I'm trying to fit generalized linear models to some sets of count data that might or might not be overdispersed. The two canonical distributions that apply here are the Poisson and Negative Binomial ...
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0answers
13 views

Comparing different estimation approaches — poisson vs negative binomial vs FE?

What's the appropriate way to compare two different estimation approaches? I've got a panel data model (balanced with states as panels and years as time) -- but it's over dispersed with a lot of ...
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13 views

Interpreting scaled betas for quadratic terms in a negative binomial regression

I created a negative binomial model where the final model included 5 quadratic predictors (each with a corresponding linear term). I am considering two ways to interpret the beta coefficients for each ...
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14 views

High Value of Incidence-Rate Ratio

after running several negative binomial models, the IRR for one of my ivars has returned consistently high IRR values ranging from 18 to 365.... All the other ivars return 'normal' IRR values and I am ...
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0answers
40 views

Estimating probability of observing greater than X events based on a current population and historical rates

Let's say I have a population that varies from month to month, and per month, there are X number of failures. Based on historical rates, I am trying to find the probability of observing Y or greater ...
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15 views

using mgfs to find limiting distribution

Can someone help me out with proving that the limiting distribution of a negative binomial (k,p) distributed variable is poisson if we let k -> infinity and p->1. I am just learning about limiting ...
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28 views

interpretation negative binomial

I have a question towards an analysis of purchasing decisions. I have a data set where I investigate the amount of previous purchases last week (predictor) on the amount of purchases today (response ...
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13 views

How do I model chapter-verse references?

Context: I am part of an 8-person group in which each person posts a Bible verse every day. For those who don't know, that is of the format "Psalm 30:1" where first we reference the chapter, then the ...
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1answer
201 views

Negative-binomial why the answer is 0.288?

In a negative-binomial experiment with three independent trials, if I want the probability for 2 successes before the first failure. The probability of each trial is 0.6. ...
2
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1answer
53 views

Poisson and NB results

i did a regression with poisson model, and since the dependant variable is overdispersed (0.13) , i have also tried negative binomial. The problem is that my explanatory variable "repeated partner" is ...
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28 views

Negative Binomial Regression 0 Problem

I am dealing with a count data set. I am trying to predict the amount of purchasers per day by the amount of previous purchasers for different products, counting the amount of purchases per day. ...
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1answer
33 views

glm.nb fails to converge when adding one zero

I have a problem where glm.nb (R version 3.1.0, MASS version 7.3.33) converges on some data, but adding only one 0 it does not converge any more. This is the data ...
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1answer
25 views

Standard error of Poisson and negative binomial regression

In Poisson and negative binomial regression, the response is assumed have Poisson and negative binomial distributions respectively. When we test the significance of the parameter $\beta$, which is ...
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33 views

Can I use SAS Copula procedure or Matlab copulafit to fit count data (Poisson or Negative Binomial)

I want to simulate data (x,y) with dependency using copula. Matlab has the function for t copula, Clayton, Frank, and Gumbel bivariate Archimedean copulas. But I am not sure if these functions could ...
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0answers
33 views

Multiple starting value/convergence warnings when running glm.nb in R

I'm running a negative binomial GLM in R. Running the model with the pooled dataset works just fine, but I'm encountering several warning messages when I attempt to run the same model for some of the ...
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56 views

WinBUGS/JAGS code for calculating Bayesian p-value from negative binomial model

I have a working negative binomial model written in BUGS code, but am not sure about the appropriate Bayesian p-value code to test goodness of fit. Specifically, I would like to calculate Pearson's ...
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21 views

How to model the following dependent variable? [closed]

If I got a dataset which the (count data) dependent variable has the following distribution, how should I model it? I am aware of the zero inflated model and the negative binomial model, but are ...
2
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1answer
43 views

Exploring effect of treatment on count data

I've collected data on animal visitation at four different points in time. The four time points represent the total animal visitations over a three day period, i.e. 3 days of monitoring at four ...
2
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1answer
32 views

Need code for sampling negative binomial with non-integer $r$

I'm trying to write code (in C) to sample from a negative binomial distribution parameterized by $r,p$, where $r$ is not necessarily integer (also called Polya distribution). I've found a number of ...
3
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0answers
83 views

simulating birth death process with random numbers from negative binomial

I am trying to generate random deviates for the population size at time $t$ for a birth-death process with constant birth and death rates per individual and initial size $N_0 \gt 0$. For the simple ...
2
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1answer
108 views

Is it meaningful to calculate predicted marginal effects of a count data model with an interaction effect?

In a little regression model of mine, I estimate the following formula a a negative binomial regression type (it would hold for a Poisson regression as well): $$ y = \beta * var1 + \gamma * var1 * ...
2
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1answer
39 views

Finding how many times I need to perform an action before I have an x% chance of a specific outcome in r

Non-specific question: There is an action that can be performed that has multiple outcomes. Each outcome has a different probably, p, of occurring. How many times, n, do I need to do the action before ...
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1answer
151 views

Choosing reasonable parameters for a negative binomial distribution

My data is a list of observations and a count for each observation. The data is overdispersed, the mean is ~1,200 and the variance is ~18,000,000. I want to use a negative binomial model to assign ...
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77 views

Zero Inflated Poisson or Negative Binomial Regression model in Panel Data

I am using the Stata version 13.1. My data is count in nature and also it is a balanced panel. However, my data suffers from the problem of excess zeros and also suffers the problem of overdispersion. ...
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59 views

Negative binomial mixed effect model for repeated measures with R - prediction and plotting

I have a dataset to analyze in which a response was recorded at the ends of months 1,3,4,5,6 in 187 patients. All patients had the responses recorded in each week, and all patients started a treatment ...
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1answer
26 views

Random Coefficient Negative Binomial Model

I have a crash count data and i want to build a random coefficient negative binomial model in R. The dependent variable will be the crash counts and covariates will be Lane width, AADT, shoulder width ...
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0answers
76 views

Modeling discrete count data with a gamma distribution

I've encountered a statistical model in which discrete count data are modeled with a gamma distribution (supported on nonnegative reals). The model relies on the property of the gamma that a sum of ...
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0answers
53 views

Negative binomial regression: Different results between the glm y x, (nbinomial 1) link(log) and glm y x, (nbinomial ml) link(log) Stata command?

I'm running a negative binomial regression. I found big differences in the results* if I compute with the glm y x, (nbinomial 1) link(log) and glm y x, (nbinomial ml) link(log) (for Stata) command. ...
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0answers
26 views

Upon transforming coefficients, how do I transform SE, z value and Pr(>|z|)?

From a Negative Binomial regression, I obtain the following coefficients: ...
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75 views

Predicted number of events from xtnbreg, fe make no sense

I am trying to compute the number of predicted events from a fixed effects negative binomial regression model in Stata. I run the model first using random effects, then using fixed effects, and ...
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0answers
53 views

Adding a square root link function to an overdispersed negative binomial GLM

I'm analyzing nematode count data (80 data points) from a randomized block design in which I have two factors with both four levels (Plant and Inoc). The data show heavy overdispersion when analyzed ...
2
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0answers
37 views

Specifying distribution in generalized estimating equation GEE

GEE allows you to identify the distribution of the outcome variable and appropriate link function. How do you make this selection in a longitudinal model where the distribution changes in time. An ...
3
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0answers
85 views

Modelling flight delays with negative values

Modelling flight delays with negative values I am working on a model to predict whether a flight will be delayed. The data consists of some explanatory variables for flights from a specific airport. ...
2
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1answer
74 views

Poisson for percentage data if values are low?

I have percentage data for diet per area (example here.....) I have no data on the individuals contributing to this diet, only for the population as a whole for each area. I want to assess ...
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0answers
23 views

Zero-inflated negative binomial regression: 0 probability of a count greater than 0

Zero-inflated negative binomial regression assumes 0s are generated by two processes: a group whose counts are generated by a negative binomial regression and a group who have a "0 probability of a ...
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2answers
179 views

Justification for using a zero-inflated negative binomial regression

I'm trying to describe in words why I used a zero-inflated negative binomial regression instead of an negative binomial regression: To model my data I used a negative binomial regression. However, as ...
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1answer
39 views

Distribution of number of Bernoulli trials before some large number of sucess [duplicate]

We repeatedly make an experiment where we count the number $n$ of Bernoulli trials of known probability $p$, until some number of successes $s$ is reached. I'm willing to restrict to $p<0.01$ and ...
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2answers
161 views

hurdle model with negative binomial distribution of counts - error message and model selection

I'm working with over-dispersed count data, which is zero inflated (~2/3 zeros). I've fit a hurdle model using hurdle from ...
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1answer
93 views

Computing repeatability from overdispersed zero-inflated negative binomial GLMMM in R

I'm trying to compute repeatability of a count response variable from a Generalized linear mixed model with multiple fixed effects and individual ID as a random effect. I'm dealing with both ...
3
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1answer
394 views

R glmer.nb output. How to get $\hat{\theta}$?

I would like to obtain estimated $\theta$ from glmer.nb function in lme4 package. In my understanding this function fits the model: $$ Y_{ij}|\boldsymbol{B}_{i}=\boldsymbol{b}_i \overset{ind.}{\sim} ...
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0answers
35 views

Does negative binomial regression assume sample independence?

I'm working with a negative binomial multiple regression and I'm wondering about the assumption of spatial independence of samples. White and Bennetts (1996) say that the assumption of spatial ...
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0answers
42 views

Trending Residuals in Negative Binomial Panel Regressions with Patent Data

A commonly faced problem for researchers working with patent data is that we need to work with negative binomial models because our dependent variable is an overdispersed count variable. I am using ...
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0answers
77 views

Modelling count data: mean-variance relationship

I have fit a poisson, quasi poisson, and negative binomial model to some count data. To ensure that I have valid models, I am checking that the following assumptions are satisfied: No ...
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1answer
99 views

choosing between overdispersed poisson or negative binomial regression

I am performing a GLM on count data (insurance claims) and I wish to compare Overdispersed Poisson Regression (ODP) against Negative Binomial regression. I would know whether there is a practical ...
4
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1answer
293 views

Feasibility of Negative Binomial Spatial Regression

I have a set of crime count data where it appears that the data take on a negative binomial distribution. I have had some success converting the dependent variable (a crime count) into a rate and then ...
0
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1answer
44 views

Regression formula for negative binomial with random effects

I am doing a negative binomial regression with random effects. I have Panel data on 23 countries ($i$) across 28 years ($t$), with one dependent, one independent and three control variables. I do ...
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42 views

what is the meaning and purpose of modeling a data?

Background: I collected a whole years access logs of my website, counted visit frequency for every user, and the numbers of user at each unique frequency, I got a distribution: $n_w \tilde\ D_w(f_w ; ...