Variables that are counts (non-negative integers) often have an excess of zeroes. Zero-inflated regression models (e.g. zero inflated Poisson, zero inflated negative binomial) are designed to deal with this. Less commonly, continuous data can have this issue, and there is zero-inflated normal ...

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How to model the following dependent variable? [on hold]

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 ...
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0answers
20 views

Appropriate test (in R) for proportion data that aren't normally distributed, aren't based on counts, and include 0's and 1's?

I'm studying differences in tree health among 5 species of trees across 3 different green infrastructure types. Here are the first few lines of data: ...
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1answer
27 views

What is the relationship between zero-inflated binomial and Bin(n,p) distribution?

Hi just could anyone explain the relationship between zero-inflated binomial and $\text{Bin}(n,p)$ distribution? I think zero-inflated binomial should be a kind of mixture and $\text{Bin}(n,p)$ and ...
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1answer
44 views

General estimating equation with zero-inflated continuous data in R

I'm running a General Estimating Equation using the geepack package in R. I'm wondering what distribution family would be appropriate for my data, which are zero-inflated and continuous. I would have ...
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1answer
52 views

How to choose between poisson regression and zero inflated models

I have data on children visiting the A&E department. I want to see which variables are associated with the numbers of visits. For instance, if genetic factors are associated with more visits to ...
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0answers
25 views

Zero-inflated mixed models with two-stage fitting

Zero-inflated models have a count component (Poisson/Neg. Binomial) and a zero component (logistic regression part). glmmADMB supports the zero-inflation feature but only through estimating a ...
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0answers
17 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
108 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
67 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 ...
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1answer
26 views

Finding a distribution for data in $\mathbb{N}_0$

Suppose, we have a set of 10,000 individuals. Each individual falls into exactly one of 200 categories. [Edit: The categories are phenotypes (different potential outcomes) of the one property that is ...
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0answers
87 views

Fitting a glm to a zero inflated positive continuous response

I'm trying to fit R glm's to data sets where the response is zero inflated positive continuous. This is an example data set ...
3
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1answer
179 views

Zero-inflated negative binomial models: why not use two separate models?

Zero-inflated negative binomial models have two components: a count component (negative binomial regression part) and a zero component (logistic regression part). Why not just run two separate ...
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1answer
109 views

How to handle zeros in target variable

I'm working on a college assignment in introductory statistics to try to predict a certain target variable. The variable is continuous but has a high percentage (60%) with zero values. This is not bad ...
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37 views

Zero-inflated mediator in a structural equation (MIMIC) model: dealing with structural zeros

My task is to estimate the impact of job change and its characteristics (e.g. voluntariness) on well-being. Well-being is measured at two time points, T1 and T2. Some respondents have changed jobs ...
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0answers
27 views

zinb estimates change when using factor variables

I use Stata SE 13 and I have a problem with the command zinb in Stata. I have binary variable female which is 1 if respondent is female, 0 otherwise (no other ...
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1answer
27 views

Zero-heavy dataset with proportional independant variable

I am examining the effect of a binary variable (rural vs urban) on my dependant variable (total mileage expense). Essentially, a person (n) will do X amount of trips in one year, and Y trips will be ...
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1answer
183 views

When to use zero-inflated poisson regression and negative binomial distribution

I have a fairly simple dataset looking at the relationship between the first nesting date of a bird in a given year (Date) and the birds overall fledgling production from that year (Fledge; count data ...
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1answer
55 views

Zero-inflated negative binomial model for true zeros

The zeroinfl function in the pscl package in R assumes that zeros include both false zeros and true zeros. I have a zero ...
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0answers
16 views

overdispersion and zero

I have run GLM and GAM for my data (Mnemiopsis leyidi) in 4 season. I have used the quasipoisson for reduce of the effect of over-dispersion. in some the papers write that negative binomial is better ...
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0answers
82 views

Zero inflated model problem: system is computationally singular

I'm using R.After getting an error asking me to provide starting values for a glm (poisson family), I took a look at my data and realized I had quite a bit of zeroes. So, I tried zeroinfl from pscl. I ...
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0answers
331 views

Interpretation of Zero-One inflated Beta Regression with R (GAMLSS)

I am not that familiar with the interpretation of a beta regression with the r-package GAMLSS. Papers and package manuals didn`t help me. I modeled a Zero-One inflated Beta Regression. The ...
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0answers
14 views

R mhurdle with same 2 predictors in 2 separate hurdles

My outcomes are zero-inflated but otherwise normal. I want to propose a model in which the very same predictors determine both whether the value is zero or non-zero, and separately from that, if ...
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1answer
117 views

Are my data zero inflated?

I'm building a function/package. If the users' entry data are zero inflated then the code will log-normalise them, process them, and reverse-log-normalise and bias-correct them afterwards. If they're ...
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0answers
68 views

Assessing the accuracy of zero-inflated beta regression models

I have fitted a zero-inflated beta regression model to my data in R, using the gamlss package. However, I am unsure of how to assess the fit of the model to my data, i.e. finding a coefficient of ...
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0answers
57 views

Multiple regression with many zero values in DV, skewed data

I am not an expert, but I am trying to run a fixed effect multiple regression model in STATA. My data is panel data and has around 12000 observations, 348 districts over 36 months. My dependent ...
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83 views

Basic idea of zero inflated two part models(hurdel) and application to big data (machine learning)

I'm currently working on the data which has 90% 0s in response variable. Based on my research, it seems zero inflated models could be a solution to this. However, while I was reading related ...
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66 views

How to model overdispersed percentage data?

this is my first post so let me know if you need more information. This is a pretty general question for now, but I am not sure how to approach this. The data I have is from an ecological study. In ...
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3answers
198 views

GLM with data piled up at zero

I am trying to run a model to estimate how well catastrophic illnesses such as TB, AIDS etc affect spending on hospitalization. Now I have "per hospitalization cost" as the dependent variable and ...
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1answer
60 views

Problems with interpretation in zeroinflated models in R

My response variable is number of Fishing cat scats and I am using a zero-inflated poisson regression model to see the effect of the predictor variables on habitat use of Fishing cats. The predictor ...
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0answers
28 views

Limits of zero-inflated negative binomial in % of zeroes

What are the limits of a zero-inflated regression? Specifically, if more than 80% of the data is zeroes, is the ZINB still valid? What is a good rule of thumb or educated way to understand the right ...
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1answer
152 views

Zero inflated negative binomial with selection

I am looking for a Stata (or R/Matlab if there's no Stata) implementation of the model described by Greene (1994) (http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1293115). It is essentially a ...
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0answers
14 views

comparing same negative binomial models built with subset data

I have a dataset made our of several stacked datasets (one for each state). I want to check whether a zero inflated negative binomial model with data from an individual state is different from the ...
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2answers
154 views

Linear Regression With Groups vs. Points - Issue with Influence of Zeros

I have a data set with two columns, the first of which is to be used as a response variable and the second of which is to be used as a predictor variable. The predictor variable, however, is populated ...
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1answer
157 views

“Zero-inflated continuous covariates”, Can they cause problems in logistic regression?

I pose a very similar question to this, although I felt the advice given does not apply to my particular situation; I am using logistic regression models for an animal habitat occupancy study, and ...
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67 views

how to fit a zero inflated NB distribution with large mu and sigma by fitdist + gamlss functions

I've been trying to figure out how to use gamlss.famliy Zero inflated functions (e.g. ZIP) on the data. A descriptive stat on my data is as follows; ...
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0answers
204 views

Outlier detection with ROBPCA for multivariate poisson/non-normal data

It is stated here[1] that we can use ROBPCA to detect outliers for multivariate data. After reading the manual ([2] page 12 : "multivariate normal model etc."), I think the ROBPCA method is also ...
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1answer
185 views

Interpretation of binomial parameters in zeroinfl in R

In the help page of zeroinfl, it says "a binary model is used that captures the probability of zero inflation." But it seems it is modeling the opposite of that ...
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1answer
463 views

Zero-inflation on steroids: choose among Poisson, negative binomial and zero-inflated regressions

I am struggling to fit alternative count models into my data. I guess my problem is just too many zeros. This is my data ...
0
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1answer
68 views

Interpreting ZINB - inflation model non-significant

I have a zero-inflated negative binomial model to a dataset (n = 47) with a over-dispersed dependent variable (...
2
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0answers
166 views

BRT predictions on zero-inflated gaussian fish abundances include negative results

hopefully someone can point me in the right direction here. I'm using boosted regression trees (BRT) to assess the relative importance of a number of environmental factors (sea bottom temperature, ...
1
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1answer
119 views

Correlations in count data

I have two count data variables X and Y that contain many zero values (90% in X, 60% in Y). I would like to check if a correlation exists between these variables, but I'm not sure how to proceed due ...
0
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0answers
107 views

Model choice for nonnegative and positive continuous right skewed outcome

I am trying to analyze a set of nonnegative continuous non-integer data (i.e. the data points are not counts) that are mostly between 0 and 3 whose distribution is highly right-skewed even after log ...
2
votes
1answer
141 views

Why NB and Poisson performs superior than ZIP, ZINB and Hurdle in presence of lots of zeros?

I am working on a data which contain nearly 80% of zeros and positive counts as large as 7. The dataset is very large, nearly 16,000 cases. It is a health related data. I have fitted ZIP, ZINB and ...
3
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0answers
36 views

Count data with one factor level containing only zeroes

I have a simple poisson glm with one predictor that has three levels. Unfortunately, for one level my response, the variable has only counts of zero. I expected very low counts (perhaps a one or a two ...
4
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2answers
195 views

Why are there no one-inflated count data models?

I am working on zero-inflated count data models using the pscl package. I am just wondering why there is no development of models for one-inflated count data ...
1
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1answer
295 views

Approaches to regression with zero inflated response

I have zero inflated response variable I am trying to predict. I am facing few issues applying different regression models that should correct for this. This is my 10,000 obs dataframe ...
0
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1answer
1k views

predict function and categorical variables in R

This is more of a general question about how the predict function treats categorical variables and how to interpret the output from predict. I have a zeroinfl model to predict the number of animals ...
5
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0answers
134 views

How can one test the assumptions of a zero-inflated negative binomial model in R? [closed]

I have fitted a zero-inflated model with a random effect using a negative binomial distribution in R, using the function glmmadmb. This is due to a large number of zeros and over dispersion. For a ...
2
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0answers
250 views

Suitable method for modelling (underdispersed?) count data with lots of zeros and long tail

I have a small data set of counts of bees. I tried a simple Poisson model without random effects but it was very overdispersed (3.95). When I fit a GLMM with random effects (using glmer in lme4) it ...
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1answer
170 views

not concave iterations on a zinb model

my name is vincenzo and i have that type of problem with zinb that you intorduce in this discussion (ZIP converges but ZINB does not. Should I drop this model?): the iterations continues to be not ...