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Questions tagged [zero-inflation]

Excessive 0's in a variable compared to a specified reference distribution. Regression approaches include zero-inflated models and hurdle (2-part) models. For count data, zero-inflated and hurdle models based on Poisson or negative binomial distributions are common (ZIP/ZINB and HP/HNB).

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Relating animal sightings with land cover - poisson, negative binomial, zero inflated and then LOST

I have a number of sightings of animals in a location (an island). The sightings are opportunistic (corpses people stumble upon) and happen in different land covers. I am supposed to investigate if ...
Miren Sanov's user avatar
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Summary of the zero-inflation model fitted with glmmTMB from piecewiseSEM [closed]

I've been playing around with structural equation model lately using piecewiseSEM package in R.There are five paths specified in the model, however some, the data of which were found to be zero-...
Ivan Raindolph's user avatar
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Am I using the right method to model my zero-inflated data?

I have a dataset of workplace permits, sample size n=3000. The data is collected between 2012-2020, so if a permit was active some time between 2012-2020, I included it in my analyses. My exposure of ...
user9410's user avatar
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zero-inflation analysis multilevel for continuos data (not count data)

I was trying to fit a multilevel model, but I discovered that my dependent variable is highly skewed and zero-inflated. Individuals report 5 times a day for 7 days their level of paranoia and the ...
miso's user avatar
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Term for non-structural-zero part of a zero-inflated model

One way to describe a a zero-inflated random variable $Y$ is $Z \times Y'$ where $Y'$ is some discrete random variable and $Z \sim \text{Bernoulli}(\psi)$, for some $\psi \in [0,1].$ My question is: ...
Noppawee Apichonpongpan's user avatar
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How to handle zero-inflated time in Cox proportional hazards model with categorical covariates?

I am using a Cox proportional hazards model to compare the time to an event, adjusting for several categorical variables (X1, X2, and X3). One of these variables, X3, is a three-level categorical ...
AziR's user avatar
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getting incidence rates from IRR using zero-inflated poisson regression

my data looks like this: and so i used zero-inflated poisson regression model to model events (e.g., hospitalization for a specific condition). ...
Yuliya Deni Krushni Nikolayeva's user avatar
2 votes
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When to include random-effects in zero-inflation model component?

Is it appropriate to specify random-effects (RE) in zero-inflation (ZI) component of the model? My intuition is that whatever RE is appropriate for main component should be appropriate for ZI ...
Suhas Bharadwaj's user avatar
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16 views

Low VIF in conditional model but high in zero-inflated model

I am using glm ZINB to make models that predict abundance of frogs based on observations from 57 sites. I used the check_model function from the performance package and it shows that the best model ...
Marco Lassandro's user avatar
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53 views

Difference between zero-inflated model and zero-altered model

Could someone explain what assumptions I am making (perhaps implicitly) when I specify family = nbinom2() versus ...
Suhas Bharadwaj's user avatar
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21 views

Binomial mixed model with conditions only ever 'succeeding'

I've been wrestling with getting some models to converge and make sense and think I've identified the problem, but am now looking for a solution (and if you agree with the "problem"). ...
igwill's user avatar
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ZIP interpretation

I am looking to improve my knowledge in data analysis and therefore in statistics. I am interested in sighting rays during underwater diving. I have a dataset that corresponds to nearly 10,000 dives ...
OBE's user avatar
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How to tweak my glmmTMB model to address several items? i.e. covariates, reference levels, random factors, and zero-inflation model

I recently ran a Zero-inflated negative binomial mixed model (ZINB hereafter) using the glmmTMB function from the glmmTMB ...
bribina's user avatar
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Confirmation that 0-inflated poisson model is specified correctly in jagsUI package

I have data representing counts of roads within a given cell of a raster (value) and I want to examine how it responds to a fixed effect of year (scaled, year_sc) and two random effects of cell ID and ...
madip's user avatar
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Exact equations for predictions in the hurdle model?

I am using the pscl package in R to fit the hurdle model for count data (default specification: binomial for zero hurdle part and Poisson for the truncated count ...
Circle's user avatar
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Zero-Inflated Dirichlet

I want to set up a model that will rely on something similar to a zero-inflated Dirichlet distribution. As such, I'm trying to figure out how a zero-inflated Dirichlet distribution is set up from the ...
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glmmTMB ZINB model non-convergence

I am looking for help with fitting a ZINB model with mixed-effects. The model which I intend to fit contains a random-intercept (three variables/terms denoting the nested, hierarchical group structure)...
Suhas Bharadwaj's user avatar
6 votes
1 answer
102 views

Small Sample Sizes and Zero Inflated Count Data in R

I am working to produce a model in R for seed germination count data with lots of zeros (around 50% of the 264 total observations). The purpose is to determine the effect treatments have on plant ...
newspice's user avatar
1 vote
1 answer
25 views

Regression with one group having just zeros as input

I want to analyse the effect of the sports membership fee on the cancellation probability with a simple regression. When a person leaves a sports club (Cancel = 1), their membership fee is ...
Stojan's user avatar
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Is it possible to run a zero-inflated negative binomial model with complete separation? [duplicate]

I am trying to analyze how the number of events Y is influenced by three factors A (4 levels), B (2 levels) and C (2 levels) and the interactions between the three. Initially trying a poisson ...
Insect_biologist's user avatar
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105 views

Interpreting a rootogram

I recently needed to use a Zero-inflated Negative Binomial and Hurdle Negative Binomial models to model some data. When finding ways to assess the goodness of fit, I came across rootograms. But I am ...
Bileobio's user avatar
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Predict customer profitability where profitability has a distribution that is zero-inflated and continuous

I have a data set of historic behavior (2 years back) attributes for about 2 million customers and I want to make predictions of the customers probabilities coming 365 days. I have about 30 different ...
Parseval's user avatar
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2 votes
1 answer
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Why the p-values of a zero-inflation model are not useful, and how do we know statistically significance?

We are talking about zero-inflated negative binomial models. In this post Ben Bolker said: The p-value in the zero-inflation term is not really useful (and should probably be eliminated from the ...
robertspierre's user avatar
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How to handle zero inflated data and incorporate random effect in beta regression?

My research question - how does the inbreeding level change in different age (life stages)? I have data of about 12000 observation done in different year (2007 to 2014) and 10 different islands (...
Nitya Shrestha's user avatar
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1 answer
72 views

Interpretation of a zero-inflated poisson model

I have the following data ...
GiorgioS's user avatar
13 votes
3 answers
877 views

When is it appropriate to use a zero-inflated Poisson regression model?

Is it appropriate to employ a zero-inflated Poisson regression model for datasets characterized by a notable presence of zeros, even when these zeros are true zeros?
Wagathu's user avatar
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1 answer
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Dependent variables are count variable with an upper bound

I need to test some hypotheses for a social sciences dissertation. In my description below, I refer to the independent as the Xs and the dependent variables as the Ys. I am expecting a straight linear ...
NutellaMonster's user avatar
4 votes
1 answer
159 views

Dependent variable is a bounded between 0 and 1

I need to test some hypotheses for a social sciences dissertation. In my description below, I refer to the independent as the Xs and the dependent variables as the Ys. I have jotted down what models/...
NutellaMonster's user avatar
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21 views

Zero inflated and right skewed dependent variable – is the Tweedie distribution a good solution?

We are conducting a variance decomposition using a hierarchical linear random effects Bayesian model to investigate the variance in a DV that is affected by three nested layers. Because the DV is ...
james_westfield's user avatar
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1 answer
71 views

Can you compare regression models using RMSE when samples have different proportions of zeros?

I am using the ranger package (which implements random forests) in R to build regression models of tree species' basal area, a continuous measure of abundance and ...
Jim Worrall's user avatar
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Error in fitting Two-Part Mixed Effects Model for Semi-Continuous Data with GLMMadaptive

I am having trouble fitting a Two-Part Mixed Effects Model for Semi-Continuous Data to my data using the GLMMadaptive package. My trail includes: 2 wines, 2 treatments, samples seven times over 100 ...
William WIne's user avatar
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How should I deal with an ordered logit model with numerous, mutually exclusive dummy variables?

I an trying to estimate an ordered logit model where the DV is a likert-scale response (1-5) and I have 6 independent dummy variables representing whether an observation belongs to one of six mutually-...
Haris's user avatar
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8 views

Analysis method for comparison of means in zero-inflated non-paired continuous data

I am currently doing my first project involving a lot of statistics and I've stumbled into a bit of a problem. I am researching if comments from two different subreddits explainlikeimfive (ELI5) and ...
Niels's user avatar
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1 answer
57 views

what is the difference between these two expressions

What is the difference between $$ \frac{exp^{-\beta_j}}{1+exp^{-\beta_j}}$$ and $$ \frac{exp^{\beta_j}}{1+exp^{\beta_j}}$$ From an application perspective ?
Ahir Bhairav Orai's user avatar
4 votes
1 answer
301 views

glmmTMB truncated models with zero inflation

everyone. I am fitting a glmm model using the R library glmmTMB for predicting a count response variable with excess-zeros and overdispersion (...
Javier's user avatar
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5 votes
2 answers
258 views

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 ...
RickyB's user avatar
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1 answer
107 views

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 ...
RickyB's user avatar
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regression model for zero-inflated pseudo-continuous outcomes with negative values and practical solution in R?

I am looking high and low for how to model data where the outcome is pseudo-continuous (change in questionnaire scores) that can be negative and has a lot of "true" zeroes. I see talk about ...
gj.'s user avatar
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Why does the zero-inflated Poisson model in R's mgcv package only display one set of coefficients?

I am using the mgcv package in R to build a Generalized Additive Model via the gam() function with the ...
geoscience123's user avatar
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63 views

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 ...
Ric87's user avatar
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zero inflation and endogeneity in logit or probit model

What is the good model for the case of bias in the distribution of the dependent variable? The dependent variable is categorical variable and one categories are dominant (about 90%). Although I can ...
Sho's user avatar
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60 views

How do I move forward to find a better model fit, help interpreting DHARMa residuals

I am trying to test if there is an effect on number of individuals depending on the proportion of a certain land use type and its management. But I don't find a model with a good fit. There seems to ...
Vevey's user avatar
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1 vote
0 answers
72 views

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: ...
Barbara Perez de Araújo's user avatar
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0 answers
91 views

How to construct homogeneous subsets table for nonparametric tests?

Does post-hoc for friedman tests or nonparametric testshave like a homogeneous subset table from SPSS? Mean doesn't represent it well so I tried using median but my data was zero-inflated so the most ...
Derf's user avatar
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1 vote
1 answer
60 views

Descriptive Statistics for Zero-Inflated Dataset

Just as titled, I'm curious as to what should you choose to represent a measure of central tendency for a zero-inflated vector or such. My background says go "mean" if normally distributed, &...
Derf's user avatar
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3 votes
1 answer
467 views

Lognormal including 0

I'm trying to model a random variable $X_i$ related to updates in prices. The updates in prices are always non-negative, and my random variable is the update coefficient. For example, if product $a$ ...
Santiago's user avatar
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40 views

Is it possible to correct a zero inflated explanatory variables in a GAM?

I am trying to fit a GAM to model a presence/absence of marine mammals in function of temporal and environmental variables using MGCV (hence using binomial distribution). My 'precipitation' ...
Patou's user avatar
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81 views

Why would a model indicate overdispersion without random effects but underdispersion with random effects? (and how to handle)

Overview: In my model building process, I fit both GLMs and GLMMs. I noticed that the GLMs suggested overdispersion in the data, while the GLMMs suggested underdispersion. How can I make sense of this,...
Reid's user avatar
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1 vote
1 answer
154 views

Relative importance in hurdle model: which metric to use?

I want to calculate the relative importance of predictors of a hurdle model, my first choice is dominance analysis. For that I would need a suitable metric of model quality. My first thought is to use ...
M. Riera's user avatar
3 votes
1 answer
248 views

Zero- and one-inflated beta GAMM (Generalized additive mixed model) in mgcv

I have vegetation cover (%) data [0,1] that includes 0's and 1's that I'd like to model with a beta GAMM, but don't understand the method for doing so. I've read that if the data includes 0's and 1's ...
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