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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Zero Inflated Poisson Regression in R

I have a zero inflated Poisson regression model I want to run R, as my data are over-dispersed and I have many zeros, but I am not sure how to set up the model in R and interpret the output. First, is ...
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1answer
31 views

Non-parametric test of difference for zero-inflated data

I have zero-inflated (~90% zeros) data which is distributed like the left-hand figure above (the right-hand figure shows how when log-transformed, the non-zero component of the distribution is ...
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7 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 ...
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12 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 ...
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1answer
33 views

linear mixed model on continuous, zero-trunctated data

I have a dataset with one continuous response variable (time), a 'treatment' explanatory variable and 5 other fixed factors: ...
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14 views

How to use ln-transformation with loads of zeroes?

I came across a method of ln-transforming exogenous variables in non-negative data sets with loads of zeroes in a lecture. With the method proposed, one simply ln-transforms the variable in question ...
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39 views

Gamma hurdle model for continuous response

I am modelling invertebrate.biomass ~ habitat.type * calendar.day + habitat.type * calendar.day ^ 2, with a random intercept of transect.id (50 transects were repeated 5 times) My response is ...
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2answers
58 views

Penalized regression with zero-inflated models

I'm currently building zero-inflated Poisson & negative binomial predictive models using the zeroinfl() function from the pscl package in R. Incorporating penalized regressions into my model to ...
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1answer
23 views

A model for technical measurement data with many zeros - pros and cons of Tweedie

I analyze technical measurement data with the aim of developing a forecasting model. The data is given as a non-negative time series (data per hour). The data looks quite wilde and contains many ...
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1answer
48 views

Dealing with zero-inflation if the data are not count data type

In the literature I found that for the count data with a lot of zeros so-called zero-inflated distributions (models) and so-called hurdle-at-zero distributions (models) could be used. The differences ...
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41 views

Zero-and-one inflated beta regression vs. binomial GLMM?

I appreciate some help with deciding whether I should (and how to) construct a zero-and-one-inflated beta regression model. I want to use R to test the hypothesis that there is a ...
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27 views

What is expected count formula for zero-inflated negative binomial regression?

My IT department wants me to translate my zero-inflated negative binomial regression model into a formula for calculating expected count which they can hard code into SQL. I'm running the model in ...
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29 views

Help with highly skewed data

I have a response variable which is highly skewed and has a high percentage of zeros. I am looking for some guidance around what modeling technique to use and the process to follow. As an ...
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0answers
54 views

What statistical test should I use for variable which has all values identical and zero?

I'm a neuroscientist and I count protein aggregates in the brain. I use tissue from MND patients with and without a certain mutation, and from healthy controls (3 groups in total). When I use healthy ...
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62 views

Marketing Data with many zeros

I am working on a marketing data which is a time series data with marketing spend done through different channels and revenue generated. The data looks like this : My data contains too many zeros ...
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104 views

How to model Zero-one Inflated Proportion Data?

I have a problem with my dependent variable, which is a proportion including ones and zeros. I am analyzing the use of a fungicide in apple farming. I have a sample of a survey of 1300 farmers and ...
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1answer
48 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
55 views

Transform response for hurdle model

I am using a hurdle model (dist=negbin, link = logit) for a dataset with multiple explanatory variables, excessive zeros and overdispersion by both, zeros and count data. The residual plots (pearson ...
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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 ...
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41 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
35 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
86 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
113 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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76 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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26 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
214 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
125 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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135 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 ...
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1answer
215 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
118 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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58 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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52 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
38 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
560 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
72 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
123 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
608 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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1answer
222 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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1answer
92 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 ...
2
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0answers
107 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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82 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
252 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
102 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
37 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
255 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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2answers
172 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
268 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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0answers
301 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
263 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 ...