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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performance::icc and iccCounts::icc_counts give different result [closed]

I have run this code: ...
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Predictive capacities of Generalized Linear Models and significance

I have the following data ...
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Incomplete formula for the glm negative binomial

My data is about the number of insects that go to treatment 1 or treatment 2, and I have the factor place, with four levels (places). Each place has a treatment and ...
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Taking the limit of a Beta Distribution to yield the Gamma Distribution

The Poisson Distribution may be obtained from the Binomial Distribution by keeping $\lambda = np$ fixed and taking the limit as $n \rightarrow \infty$. Similarly, the Gamma Distribution may be ...
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Clustering and segmented regression interrupted time series analysis

I would like to perform an interrupted time series analysis to look at the impact of the pandemic on cancer incidence using individual level data. I plan to use a negative binomial segmented ...
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transforming a continous respond variable into a discrete one

I am visually estimating fish length underwater to convert it in fish biomass by means of proper length-weight relationships. Obviously, my accuracy is not perfect. When making hypothesis about ...
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How to construct confidence intervals for difference of means in logs

I have estimated an OLS model and a Negative binomial model of ln housing search (ln S) per unit (for instance, the average number of visitors per house or bidders per house) as a function of ...
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From overdispersion to underdispersion: comparing linear regression models with DHARMa

I have been investigating the relationship between the occurence of certain weather phenomena and time. To aid me in evaluating the fit of my (simple linear-regression) models, I have been using the ...
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Can I use the Negative Binomial distribution to calculate the max number of trials where I have less than X fails with some confidence?

Thank you in advance for any help. I am trying to compute the maximum number of times I should expect to attempt a Bernoulli trial to keep my number of fails (with probability of failing $p$) under ...
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The sum of two Negative Binomial variables doesn't follow a Negative Binomial

I assume that the number of home corners and away corners would follow the Negative Binomial Distribution and I expect that these two variables have the same parameter ...
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Can a covariate also be a random effect in glmmTMB model with ar1 [closed]

I have data consisting of catches of insects at weekly intervals over 2 years, repeated with the same methods at the same location 3 decades later. My main question is, have numbers (total and for ...
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Distribution of a conical combination of n poisson variables?

Does a conical combination of n Poisson distributed variables have a closed-form distribution (linear combination with nonnegative coefficients)? I know that the sum of random Poisson variables would ...
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Theoretical justification for using a zero-inflated count model

I have a theoretical question regarding the use of zero-inflated models. There are similar questions here and here, but neither answer set seems to deal with the theoretical question I am asking. I ...
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Stata and R giving different results for zero-inflated negative binomial regression [closed]

I know this has technically already been asked here, but it doesn't look like the previous question had a reproducible example. I am having the same problem: Very simple, running a zero-inflated ...
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What probability would I use in a negative binomial distribution to say the expected number of false identifications per true identification?

I have binary classifications made by some model, and I know the truth. From this, I can calculate the confusion matrix and all associated values: true positive rate, true negative rate, false ...
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Negative binomial for catch data with GAM

I work with landing data (kg or tons), which don't follow a normal distribution and are more often than not over-dispersed. I'm trying to obtain a standardized index of abundance using GAM to model ...
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Rule of thumb for deciding between Poisson and negative binomal models

I am analyzing the number of a specific class of mutations in cancer genome sequencing data, as a function of: (1) overall mutation rate per sample, (2) length of the genomic segment (gene) being ...
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Negative Binomial Regression Model - Effect of Removing Significant Covariates

I have been dabbling in NB regression for less than a year now. I have applied the well known g.o.f. tests. Lately I started using the Conditional Moment (CM) test, described in Cameron and Trivedi ...
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Statistical test whether data conforms to a spatial point process--gaza bombing locations

I came across this image on twitter, and it made me think about testing a point process hypothesis. Now this is a politically sensitive image, and I don't want to run afoul of any SE posting ...
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MGF of "generalised" Negative Binomial distribution

Would the "extended" Negative Binomial have the same MGF as Negative Binomial? (See the definition of "extended" Negative Binomial below by Wikipedia) Could someone please help ...
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How to report negative binomial results with a multi-level categorical variable?

I would like to ask 2 questions: the first, as indicated in the title, concerns how to report the results of the 'negative binomial model'. The second, differently, relates to how to interpret the ...
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GLMM optimised with CG gives empty warning, diagnose() finds no problem

I am running the following code for a ZINB GLMM, using the glmmTMB package in R: ...
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Generate sample from negative binomial distribution with fixed sum

Building on this recent post Generate sample from poisson distribution with fixed sum answered by @Henry and @Xi'an, how could we similarly go about generating n random samples from a negative ...
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Probability generating function and binomial coefficients

I'm reading an article where the authors derive the mass function of a compound distribution by considering the generating function. The generating function of interest for a random variable $N$ is a ...
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Is it possible to add a regression/fitted line equation to a mixed-effect model plot?

I have been asked to add a regression/fitted line equation to a negative binomial mixed effect model plot. Example of a regression line equation is highlighted in yellow below for ...
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Overdispersed and zero-inflated count data

I have a dataset with social media posts and like to predict the number of likes a post receives. So I fit a Generalised Linear Model (GLM). I am relatively new to GLMs but find them super cool. ...
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How to interpret the average rate of NB-GLM when offset is involved?

My question is on how to interpret the coefficients of a negative-binomial GLM that included an offset. My dataset is a clinical trial where patients got one of two treatments (A or B) and stayed in ...
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Need guidance in missing value imputation in count variables

I have a few count variables that are part of a larger dataset (the rest of the variables are either numerical or ordinal). Their distributions can be seen below. My goal is to impute the missing ...
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Should point estimates for a parameter always be exactly in the middle of their 95% CI or does it depend on the distribution? [duplicate]

I'm modelling some count data using negative binomial regression with glm.nb in R. I've noticed that my point estimates are quite consistently not at the midpoint of the 95% CIs and wondering if this ...
Anthony Fish Hodgson's user avatar
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297 views

Understanding emmeans outputs for poisson and negative binomial GLM fitted on count data with or without offset

I fitted a poisson and negative binomial GLM on count data (=larva) and try to explain it as a function of a factor (=modality). However, as the traps used to trap larvae from inflorescences were ...
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sample size and covariates connection

Currently I am applying negative binomial regression. My total sample size is 669 as this is a follow up data. Count variable (dependent variable) is mental health visits, primary independent variable ...
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Test for significance in count data

I have count data as below. I want to check if the counts (freckles) between conditions are statistically different in each type (using R). For each condition, we aim to recover 10,000 cells. I guess ...
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Help interpreting zeroinfl results from emmeans

I am working on the example Senecio data from Blasco‐Moreno et al. (2019) using the pscl package in R. I would like to conduct pairwise comparisons of mean rates (Damaged/Total_heads) and don't ...
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How to interpret interactions involving quadratic terms in a GLM?

I'm trying to interpret the output of a GLM from a tutorial that models species abundances as a function of environmental data and species traits. The function ...
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Negative Binomial Model Generating counts

I am working with crash data that measures injury severity using the values 1, 2, and 3, which correspond to Fatal, Seriously Injured, and Slight, respectively. I am attempting to use a negative ...
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sample size calculation of random coefficient negative binomial regression

Please help me with calculating the minimum sample size of random coefficients for a negative binomial regression. I am wondering if a group receiving an intervention will have a significant ...
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Interpretation of glmmTMB output for zero-inflated negative binomial regression

I fitted, using glmmTMB R package, a zero-inflated negative binomial GLMM, with offset and a random factor, to investigate which variables could explain animal ...
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Dealing with non-independence in data in negative binomial regression

I am evaluating an intervention that reduces seclusion in mental health care wards. So, I will be using negative binomial regression to determine if there is a significant difference between ...
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include length text as covariate or offset in negative binomial regression model

I have a dataset that contains the number of devices used to express casual relations in a text. I've constructed a Negative Binomial Regression to estimate the effect of Educational Level (3 levels) ...
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GAM negative binomial model improved by log-transforming the dependent variable

I fit a negative binomial GAM model with the R mgcv package. I noticed some heteroskedasticity in the fitted vs response plots. Then I noticed that if I log transform the dependent variable before ...
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Nb/Poisson regression with weighted survey data resulting in counts with decimals

I am analysing suicide counts and thus it seems appropriate to use Nb/Poisson regression. However, my counts come from survey data and are only whole numbers when unweighted. Once I realise the ...
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Error when using R zeroinfl on negative binomial count data model

I want to model number of plants in 12 different areas. Each area is divided into smaller plots of equal size for all areas. The number of plots between areas vary (31 for the smallest area, 500 for ...
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Should adjusted models produce narrower CIs than crude ones? What does it depend on?

I am working on a research project for my Masters in Public Health which compares suicide rates across different time periods. I have done all my analysis in R and from what I can tell everything is ...
Anthony Fish Hodgson's user avatar
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PROC GLIMMIX Simple Slopes Neg Bin

I'm attempting to plot simple slopes of my neg binomial from PROC GLIMMIX. I've been using the resources from UCLA (https://stats.oarc.ucla.edu/sas/seminars/analyzing-and-visualizing-interactions/) ...
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Joint Distribution of Correlated Binomial and Negative Binomial Variables

Let $x$ and $y$ be correlated negative binomial distributions, $x\sim~NB(p_1,n_1)$ and $y\sim~NB(p_2,n_2)$ respectively with correlation $\rho$. Can we derive their joint distribution analytically? ...
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How to choose between a count model and spatial error model

I have a dataset with spatial grid cells. After performing some spatial diagnostics (Moran's I, LaGrange multiplier tests), it seems that there is spatial dependency in the form of spatial error, so a ...
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Shape parameter vs dispersion in a negative binomial distribution

For data in a negative binomial distribution, is it possible to derive the dispersion if you only have the mean and shape? I don't have the actual data, just the results summary of mean and shape, but ...
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How to deal with zero inflated panel data?

For a research project, I created a panel dataset that counts violent events in subnational administrative units from 2000 to 2015, thus my unit of analysis is district-year. Out of 20.000 district-...
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Why does this General Linear Model think random Negative Binomal values have a slope?

I'm just exploring Generalized Linear Models for the first time, and trying to see if I can correctly fit the simplest model I can think of. So I'm generating random values from some NegativeBinomial ...
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Is Repurchase period in days a count variable?

So I am doing a project where the response variable is the number of days in which a product is rebought. Explanatory variables are the weight of the product, serving size etc. So basically I am ...
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