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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1answer
11 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 (...
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0answers
8 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, ...
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1answer
29 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 ...
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0answers
15 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
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1answer
40 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 ...
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0answers
19 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 ...
3
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1answer
81 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 ...
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1answer
34 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 ...
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1answer
77 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 ...
3
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0answers
32 views

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

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 ...
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0answers
61 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
21 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 ...
2
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1answer
97 views

Comparing the distributions of two processes, one of which is constrained by zero

I have two continuous stochastic Markov processes: the concentration readout of two proteins in a cell over time. These are shown in this figure, where the blue line is the unbounded protein, and all ...
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2answers
67 views

Zero-inflated two-part models for semi-continuous data

I am trying to study predictors of companies' pollution output of some specific chemicals. The data I am using have many 0's (i.e., the company did not pollute at all with those chemicals) and then ...
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0answers
138 views

Trouble finding good model fit for count data with mixed effects - ZINB or something else?

I have a very small data set on solitary bee abundance that I am having trouble analysing. It’s count data, and almost all the counts are in one treatment with most of the zeroes in the other ...
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1answer
50 views

How to calculate the expected zeros in a Poisson distribution?

I am modelling the nights spent at hotels (count data) fitting a few predictors in the model. I'd like to know how to calculate the expected number of zeros in this distribution, as I suspect that I ...
2
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0answers
17 views

Statistical test for zero valued variable

I am testing a product (liquid bag) for leakage and my primary variable is the amount of leakage in ml. I have a specification that states, on average, leakage must be below XXml. In total I tested 20 ...
3
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0answers
45 views

How to model continuous predictor variable, $x\ge0$, showing continuity “jump” at $x=0$?

I'm modeling hospital inpatient stays with a logistic regression model, and have encountered a number of predictor variables measuring # of outpatient care episodes which have an inflated number of ...
1
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1answer
90 views

Comparing two groups with many zeros

I am comparing the difference in time-activity-budgets of two populations of seabirds, those in the presence of ship disturbance and those not in the presence of ship disturbance. Focal animals were ...
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0answers
29 views

How to model zero-inflated continuous response using categorical predictors - preferably resulting in multiplicative parameters

I'm having trouble finding a suitable model for predicting the AVG value (revenue in cents) of a single click on a product on a large e-commerce site. (assuming a click leading directly to a purchase ...
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4answers
190 views

What is the difference between zero-inflated and hurdle distributions (models)?

I wonder if there is a clear-cut difference between the so-called zero-inflated distributions (models) and so-called hurdle-at-zero distributions (models)? The terms occur quite often in the ...
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2answers
119 views

Response variable: percentage and too many zeros (zero inflated Poisson?)

I am analysing the effect of density (categorical), gonad mass (continuous) and temperature (continuous) on the percentage of acini spawning in a gonad. My replicate unit is a scallop. As my response ...
2
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1answer
116 views

Why am I not able to fit a zero inflated poisson distribution?

Following what is suggested here http://stackoverflow.com/questions/7157158/fitting-a-zero-inflated-poisson-distribution-in-r ...
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1answer
64 views

Defining a threshold for percentage data with high amounts of exact zeros

I am trying to analyse my biological data which is derived from flow cytometry and describes the percentage of cells with a certain property. Data is available for two conditions: once the cells ...
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0answers
43 views

How to interpret the coefficients for binormal part in zero-inflated regression?

use zeroinfl {pscl} I specified offset only for the poisson part. The regression estimate zeroes using regressor zeros ...
2
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1answer
60 views

Zero inflate models vs generalized mixture model

Hi I am looking to compare the fit of a zero- inflated mixture model and a poisson mixture model, the random effects in both models are different. Comparing the fitted values of both models ignores ...
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1answer
110 views

Undefined real result in a zero-inflated negative binomial

I have run a zero-inflated Poisson model in WinBUGS without problems, and now I am trying to run its equivalent negative binomial. However, I get an "undefined real result" trap message over and over. ...
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0answers
56 views

How to spot if model is zero inflated?

I'm running a linear regression. The response variable is a proportion, and has quite a lot of zeros. The predictor variable is normal distributed. My two variables look something like these: ...
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0answers
69 views

Zero-inflated negative binomial

I am trying to understand zero-inflated negative binomial regression. My impression is that if a zero-inflated negative binomial model does not contain any logit part, the model is identical to the ...
0
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0answers
131 views

Modelling zero-inflated percentage data in R

I have a response variable of percent cover of vegetation in a quadrat. I have tried to arcsine square this data as recommended in the Crawley R book but I am not getting good fit. The data is ...
2
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0answers
89 views

Log-linear or poisson model with R [closed]

I have a data.frame (myData) with 6 variables which are: ...
2
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1answer
116 views

How can I fit a zero inflated poisson model with only offset (without coefficients)?

I have already got a poisson estimated lambda, and actual result y, and I would like to see if the model is good. To start with, I check if the dispersion is ...
23
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2answers
1k views

Diagnostic plots for count regression

What diagnostic plots (and perhaps formal tests) do you find most informative for regressions where the outcome is a count variable? I'm especially interested in Poisson and negative binomial models, ...
4
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1answer
187 views

Enormous SEs in zero-inflated negative binomial regression

I have overdispersed count data where the outcome is events (occurrence of a rare disease) and the covariate of interest is season. The unit of analysis is the number of events occurring in a ...
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0answers
48 views

Bootstrapping for zero-inflated models

I have been working through the code provided in the following post (http://www.ats.ucla.edu/stat/r/dae/zinbreg.htm) and applying it to my own data set (on the number of asthma attacks suffered). I ...
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0answers
48 views

Getting started with VGAM::vglm

Trying to fit a zero-inflated Poisson model, I have trouble to understand the parameters to the vglm function in VGAM. As an ...
1
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1answer
123 views

Calculate pseudo-$R^2$ from R's zero-inflated negative binomial regression

I'm looking into calculating a Pseudo $R^2$ used McFadden's method for a zero-inflated negative binomial regression. I'm unclear how to go about evaluating $\hat L(M_{intercept})$ in R. Any ...
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3answers
75 views

Which equation will give me meaningful insight?

I have 10 iPads. I am logging the number of times an app is crashing each day for each of these iPads. The number of crashes tends to be skewed towards just a couple of the devices such that taking an ...
0
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0answers
40 views

Modelling the zero-inflation parameter in a ZIP regression model

I have data from two agricultural experiments, one on 101 sites, the other on 97 sites. In both experiments, the response variable, $Y$, is a count, with an excess of zeros and there is a binary ...
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0answers
74 views

Sample size determination for zero inflated Poisson population

I'm trying to determine an adequate sample size a test with frequency data that seems to be a good candidate for a zero-inflated poison distribution. I can't find very much freely available literature ...
0
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0answers
50 views

Negative binomial or Dirichlet regression - multiple DVs

I am researching a clinical study, where I am interested to see if high/low score on these 14 psychological constructs such as hostile attitudes (continuous, neg/pos values) can predict treatment ...
5
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0answers
168 views

Stuck at analyzing large and complex data set

I've got an extremely large and complex dataset and getting frustrated with the analysis. In essence, my target question is a simple one. I am comparing insect flower visitation on >30 plant types. ...
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1answer
486 views

Modelling zero-inflated proportion data in R using GAMLSS

I am new to the gamlss package and would like to check that I am using the correct family for proportion data (tree species cover after treatment), which is bounded ...
0
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3answers
90 views

Normality of a lognormal variable having a spike in 0?

I have two very right-skewed datasets which I must study for difference in means. Given the skewness, I transformed using log 10 scale after adding 1 to be able to take the log. In other words: ...
0
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0answers
203 views

“Zero-inflated” predictors in regression?

I know that zero-inflated models (e.g. zero-inflated Poisson or negative binomial models) can be used for dependent variables. I also know that in general there are no assumptions for the independent ...
4
votes
1answer
164 views

Explanatory variables with many zeros

I am trying to fit a linear model to a price response variable. Many of the predictor variables consist of mainly zeros. For example, one possible predictor variable is "drill holes". Not many parts ...
1
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1answer
334 views

Zero inflated Poisson model

I am working to investigate association between environmental pollution and daily hospital admission due to various causes. This outcome data has excess zeros on days when there are no admissions ...
4
votes
1answer
469 views

Please help me refine this zero-inflated negative binomial model

I have been working on a baseball model to predict success at the major league level using minor league statistics. After posting multiple threads on this site (1, 2, 3) and receiving valuable ...
4
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0answers
682 views

Fitting a zero-inflated negative binomial regression with R

In this thread, I laid out a problem involving fitting a model that attempts to use minor league baseball statistics to predict success at the major league level (explained in full in the thread). ...
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0answers
236 views

zero inflated binomial data

I am working with presence/absence data that contains lots of zeros. What is the best method to model this. The only suggestions I can find for zero inflated data refer to count data not ...