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

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6 views

McFadden pseudo R squared on GLM.NB

I have used the McFadden pseudo R squared on a negative binomial glm (family=poisson). I was wondering if it's appropriate. I have found informations suggesting McFadden is useful for poisson glm but ...
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9 views

Iterative Maximization issue in Truncated Negative Binomial Regression in Stata

I was running truncated negative binomial regression in Stata and got a problem. During the iteration process, my results show " backed up" at the end of final iteration which means Stata could not ...
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0answers
11 views

Truncated Negative Binomial Regression (Stata): Missing/Blank Significance value

I was running truncated negative binomial regression (tnbreg) in STATA and got the answer but when I added [pweight = weighting variable ] to weight dependent variable to address endogenous ...
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0answers
8 views

Probability of Pr(N=0) as function of Panjers (a,b) parameters

Is there a way to find the general formula for Pr(N=0) as the function of Panjers parameters a and b for Binomial, Negative Binomial and Poisson distributions? It is possible to show e.g. parameters ...
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15 views

R hurdle and vuong tests giving strange results

So I'm trying to fit a hurdle model with the count distribution as negative binomial. I get the following outputs for assuming negative binomial and poisson: ...
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83 views

Model a Process using a Negative Binomial Distribution?

We have a random process that may-or-may-not occur multiple times in a set period of time $T$. We have a data feed from a pre-existing model of this process, that provides the probability of a number ...
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1answer
24 views

Panel count data, choosing between xtpoisson cluster-robust versus negative binomial

I have a panel count data and I would like to estimate it with fixed effects. My data shows a little bit of overdispersion (when fitted with quasi-poisson the overdispersion parameter is 5.01 and the ...
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1answer
28 views

Calculating OR and IRR for a zero-inflated negative binomial model from estimates

I used the PSCL package to run a zero-inflated negative binomial model on some count data I have. This package gives the following output: for the zero part of the model: ...
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0answers
9 views

Separating zero mean from other means

I have counts as responses to a treatment with several levels including a positive and a negative control. The positive control has a mean value approximately 10 times the 2nd highest mean; while the ...
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0answers
9 views

Can I run a system of equations (3SLS) with one linear and one nonlinear regression?

I am investigating determinants of investments (in mio. $) in a sector and determinants of technology developments (patent count) in the same sector. The study is a panel study over 50 countries and ...
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1answer
14 views

Frequency Data, Model Choice (Poisson with Offset, Fractional Regression)

I have text data and am interested in estimating the effect of some covariate on word frequency. All the frequencies are very small. The unit of observation is a single document. I'm trying to think ...
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0answers
8 views

Computing a growth rate starting from a negative-binomial-regression coefficient

I need to estimate the growth rate of a factor in time. The available information consists of a coefficient from a negative binomial regression, where this factor is the dependent variable and time is ...
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9 views

Counts vs. percentage of predictor variables in the presence of an offset

The case: I am using negative binomial models to predict the number of deaths per household for four African countries. I am using an offset (log number of household members) to obtain estimates of ...
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0answers
10 views

Buy Till You Die(BTYD) - Individual LTV scores

I'm using the Buy Till You Die(BTYD) package in R to predict LTV (using Pareto/NBD), and I've been able to produced expected transactions by week, but is there a way to predict the dollar value of ...
10
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1answer
211 views

Diagnostics for generalized linear (mixed) models (specifically residuals)

I am currently struggling with finding the right model for difficult count data (dependent variable). I have tried various different models (mixed effects models are necessary for my kind of data) ...
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1answer
33 views

How to Include an Independent Variable with one-half 0s, one-half non-0 values

I am running a negative binomial regression. One of my independent variables is a measure of distance traveled - half of the observations are 0 because they do not travel, while the other half have a ...
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1answer
25 views

Dispersion parameter in GAM output

I have a question about Negative Binomial distribution. I’m modeling a count data, as following example: ...
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0answers
42 views

RESET Test in R Influenced by Heteroskedasticity in the Data?

I'm running a negative binomial model in R on 558 observations of count data, along with "vcov" to add robust errors. I am using the Ramsey RESET Test as a criteria to judge my model. I have always ...
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0answers
58 views

Simulating data from negative binomial model (in R)

I'm modeling after this answer in order to simulate data from a negative binomial model where both y and x are counts best described by a negative binomial distribution, and am wondering if this was ...
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1answer
35 views

count data that does not fit anything

I am trying to build a counts model but my response does not seem to fit anything. If I pull the histogram looks poisson-ish but when I run goodfit() in R, it does not fit poisson or negative ...
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0answers
8 views

Regression coefficients versus marginal probabilities

I ran a negative binomial regression model and found significant coefficients for several key variables. I also ran the model as a zero inflated negative binomial model, and didn't find significance. ...
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0answers
19 views

Negative Binomial GLMM speedup

I'm using R to fit a generalized linear model with random effects using a negative binomial distribution. One of the main issues is that to run glmer() with a negative binomial, the dispersion ...
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0answers
28 views

Relationship between dispersion statistic and variance in count data models?

I am struggling to get my head around the concept of data dispersion, particularly relating to count models. Take for example, the Poisson regression model, I will often read that if the variance of ...
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0answers
19 views

AIC of a mixture distribution

I'm trying to reproduce this paper: http://core.ac.uk/download/pdf/6394955.pdf where a latent class model/finite mixture model is used on the RAND Health insurance data. The data is freely available ...
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0answers
63 views

Non-normality of residuals in a negative binomial GLMM

I am testing for the effect of treatment and fish length on the school size of fish. Treatment is a categorical variable with two levels (e.g., treatment A & treatment B). Fish length is ...
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1answer
45 views

(How) Can I compare the relative importance of coefficients on different population groups in negative binomial regression?

I am trying to determine the relative importance of about 20 different environmental factors on people's behaviour. Behaviour is either exhibited (success) or not (failure). The dataset describing ...
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14 views

Exact confidence intervals for NB linear regression

New use here so please forgive me if I am not following all protocols in asking question. My question is how to get exact confidence intervals (CIs) for the fitted values of a negative binomial ...
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1answer
79 views

R: glm.nb and when to consider using an offset or including a covariate

I'm using glm.nb to test for differences in the likelihood of accumulating overtime hours among employees across multiple departments. Department is the only information I have on which to base a ...
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76 views

R - How do the methods in goodfit() (package vcd) calculate degrees of freedom?

I have counts and I am trying to determine if they conform to the negative binomial distribution. I am using goodfit() from the vcd package, however the two methods are giving me conflicting results: ...
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37 views

Negative Binomial Regression with variable constraint?

I am working with a negative binomial regression. The data frame contains 38 predictors and 48 records. After variable selection I used only 8 variables. Finally, I got some good results. Here is the ...
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0answers
28 views

Negative binomial mgcv

I’m modeling count data using negative binomial distribution in mgcv package. I would like to know what is the best approaches: 1) nb: automatically estimates the Theta parameter; 2) negbin: ...
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0answers
58 views

Plotting predicted number of events from panel poisson and negative binomial regression models

I'm new to both poisson and negative binomial regression models, and am trying to predict a monthly count based on a panel dataset in Stata. I've already set my id and time variables using ...
9
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2answers
147 views

Scale variable as count data - correct or not?

In this paper (freely available via PubMed central), the authors use negative binomial regression to model the score on a 10-item screening instrument scored 0-40. This procedure assumes count data, ...
0
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1answer
35 views

Different results in cox model and negative binomial?

I am confused about a problem in my research. Can anyone give me some advices ? I used a Negative binomial ( in MASS package) to examine the effects of 3 covariates on dependent variable ( number of ...
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1answer
35 views

Test for significance with multivariate, highly-skewed, discrete data

The data The dataset comprises 10 variables: waiting times (rounded to minutes) for questions to be answered on Stack Overflow by programming language. Each is discrete, none is normally distributed ...
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14 views

Selecting an appropriate link function for zero inflated negative binomial regression

I have count data distributed according to zero-inflated negative binomial RV. I have been able to find good sources for a lot of model diagnostic steps, but there are a few things that are eluding ...
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3answers
586 views

Negative binomial distribution vs binomial distribution

What is the difference between the negative binomial distribution and the binomial distribution? I tried reading online, and I found that the negative binomial distribution is used when data points ...
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0answers
21 views

How to obtain corresponding p-values for count data assuming a negative binomial distribution?

Unfortunately I have basic knowledge of statistics. I have an issue with the analysis of my data. Briefly, I have a vector of counts (values from 0 to n, they can be also non-integers). I would need ...
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0answers
33 views

How to manually calculate fitted values in zero count models?

I'm looking to see if I can manually calculate the fitted values for a Hurdle model (from the pscl package) to ensure I understand what's going on, but so far I ...
0
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0answers
101 views

How to compute intraclass correlation (ICC) for THREE-level negative binomial hierarchical model?

I'm using lme4 in R, and I have a model set up that uses a three-level hierarchy for a negative binomial regression. There is previously a question (How compute the Intra-Class Correlation for a ...
15
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2answers
272 views

An impossible estimation problem?

Question The variance of a negative binomial (NB) distribution is always greater than its mean. When the mean of a sample is greater than its variance, trying to fit the parameters of a NB with ...
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0answers
20 views

Negative binomial distribution & Bernoulli distribution - expected value, MGF

could anyone please help me with the following exercise? Let us assume that the random variable $N$ has a negative binomial distribution $P(N=n) = (n+1)(\frac{3}{4})^2(\frac{1}{4})^n$. $X_1, X_2, ...
3
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2answers
43 views

Choosing between count and linear “fixed effects” models when within-variation is not skewed?

Is it appropriate to use a negative binomial regression with fixed effects when the dependent variable appears somewhat normally distributed within each group, but the overall distribution of the ...
1
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1answer
37 views

Reciprocal Causation in Panel Data

I have weekly data on stop and searches for all London Boroughs for ten years (N=32, T=566) and am interested in whether the number of stop and searches has any impact on crime rates. I don't expect ...
2
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0answers
68 views

Combine confidence intervals for daily predictions from Poisson/Neg. Binomial GLMs

I have a number of Poisson GLMs relating a daily count to daily weather predictors. They've been assembled in R from time series of counts and observed weather, and they're represented by GLM objects ...
2
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0answers
32 views

An alternative to a regular poisson distribution for count data.

I'm trying to find out what distribution my empirical count data fits. Scores can run from 0-8 and I have ~360 observations. I've been using the fitdistrplus ...
0
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0answers
37 views

Negative binomial in R

I run the negative binomial regression in R for my model (MODEL1 <- glm.nb(y ~ x1 + x2 + x3 + x4 + x5 + x6 + x7 + x8 + x9, data = mydata) and it gives me the ...
11
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1answer
485 views

Why is a “negative binomial” random variable called that?

I don't understand why the "negative binomial" random variable has that name. What is negative about it? What is binomial about it? What is negative-binomial about it?
0
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1answer
57 views

How do you deal with overdispersion in a zero-inflated negative binomial regression AND when you expect data to have zeros?

Background: I am analyzing the effect of multiple variables (lineage, ancestral plant species, plant species reared from, larval density, body mass) on different traits: ovigeny index (initial egg ...
0
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0answers
49 views

Choosing between Zero Inflated Negative Binomial model versus Logistic Regression

Context: this is in the field of genome wide association studies. The norm in the field is logistic regression, but we have high quality radiographic data that gives us counts of damaged joints, so I ...