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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analysis of variance on zero inflated semi continuous data

I have a fairly fundamental problem with my data, they do not suggest that they were sampled from a normal distribution. This is problematic because I would like to run some sort of analysis of ...
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What model is appropriate when a non-negative, continuous dependent variable has frequent zero-values because of limited data?

I'm modeling how likely a song is to occur in a playlist with a particular title. I can calculate a simple probability based on my current data, but it's highly zero-inflated because my data is ...
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zero inflated interval data

looking at the survey my data set is based on, my dependent variable originally is given in percentage ranging from 0 to 100. Howewer, in my dataset the information is categorized in to 9 intervals. 0 ...
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What is the impact of excess zeros on poisson regression coefficient estimates?

The background I have a dataset with some zeros - based on how I segment my data, it is either 50% of the observations or 80% of the observations. The data is not actually count data, but from what i ...
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Variable selection in zero-inflation models

I am trying to understand how to perform model comparison between different count models. In this example the author performs a zero-inflated poisson model testing the effect of number of people in a ...
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38 views

How to plot estimate + raw data of a Bayesian zero inflated poisson?

GENERAL QUESTION: How to back-transform estimates from a zero-inflated poisson to obtain the original scale in R? (I tried exponential like for poisson but the results are wrong) DETAILED ...
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R - zero biased data, glmer.nb, properly counting confidence intervals

any suggestions how to count confidence intervals from zero biased data? I've counted generalized linear model using glmer.nb function. I have to make graph but I was told that confidence intervals ...
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1answer
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How to model a zero-inflated 'continuous' response data in r 'without' assuming an underlying normal distribution?

I have a weather data set with rainfall as response. It has 56% observations as 0, while the rest as continuous rainfall data. I can't use tobit, hurdle or any other zeroinfl() model as they require ...
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How to calculate ICC for a zero-inflated negative binomial model

I did a zero-inflated negative binomial regression on some data. However, the data is nested (students within schools), and I would like to calculate ICC to make sure that we did not need to take this ...
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How to optimize statistical approach in terms of reducing number of statistical tests used?

I need to analyse second step care among very heterogenic patient population whose second step care is also very diverse. I can do this using multiple models and tests (up to 10), but this is just too ...
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Approach to Analyzing Semi-Rare Events

I am often faced with analyzing data that follow a pattern as shown in a mock example in the image below. Key data characteristics: for any value of the predictor (e.g. temperature), the most ...
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Hurdle model vs left censored model

When dealing with response variables that have lots and lots of zeros, is there a clear argument for when hurdle models are preferred and when left censored or tobit models are preferred?
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What regression type for Normal DV and count data IV (with lots of 0s)

I'm performing regression on subjects' response to a question on a 1-5 likert scale (1=low, 5=high, etc)- This is the DV and its continuous and normally distributed. The IV is a count of how many ...
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118 views

Model selection: Two-Part Mixed Effects Model for Semi-Continuous Data

I have now been studying mixed models for about a month, I am still a pure beginner. I have zero inflated semi continuous dependent variable (yield of trees between two periods). Exploring ...
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1answer
46 views

How to interprete the p values of cos and sin terms in periodic regression?

I have camera trap data where for each site and hour I have the abundance of wild herbivores. I want to create a model where I can estimate the effect of predator activity on the activity and behavior ...
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Choosing error function for regression

I have a dataset with ~100K samples and non-negative continuous target variable. 99% of target values are zeros and the remaining 1% are right-skewed. Here are the deciles (0 and 1 correspond to min ...
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1answer
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Extremely large (>10000) value of theta in hurdle model

I am estimating a hurdle model with a binomial (first stage) and truncated poisson distribution (second stage). The results look fine but I have a very large value of theta (greater than 10000). I ...
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How to model zero-inflated mass data? [duplicate]

I am working with a data set of the mass of plastic found at various sites. At most sites, we found no plastic and so the data is zero-inflated (see histogram below). I want to model the data using ...
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Zero-inflated Poisson regression with `unit` and `time` fixed effects (Application in R)

In much need of some assistance. My question concerns the conceptualization of zero-inflated Poisson regression in a two-way fixed-effects settings. I have crime data and my outcome is 'count' ...
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1answer
32 views

Conflicting residual diagnostics for GLMM for binary data: zero-inflation

I fitted a mixed logit model with crossed random effects in lme4_1.1-21::glmer to some experimental binary data. The maximal random-effect structure justified by ...
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Computational error for zeroinflated negative binomial regression model

I am trying to fit a zero-inflated neg. binomial model. I have many predictors for the count model, but only one for the zero model (Saturday). ...
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Zero-inflated model with no variation in the outcome

I want to fit a zero-inflated neg. binomial model using zeronfl(outcol ~ vm + Thursday + Saturday |Saturday + Thursday + vm, data, family="negbin") from the pscl ...
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How to conduct a principal component analysis on data set with large number of zeros

I have data for percentage cover of plant species in 500 sites. There are columns for 30 different species in the data set and I would like to drastically reduce this down to a manageable number of ...
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Which model should I use? (genomic problem)

I have problems with choosing which model / link function should I use for my analysis. My response: numbers from -100% to +500% (increase of tumor after therapy, may switch to ratios or log-ratios, ...
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zero inflated presence absence binomial GAM in R

I am fitting a binomial GAM using mgcv in R. My data is presence (1)/ absence(0) of dolphin acoustic detections in 10 minute time windows over ~1 year period. However, I have only ~750 presences to ~...
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DHARMa diagnostics: testDispersion and testZeroInflation interpretation

I have been analyzing count data using Poisson distribution in glmmTMB, and just ran some DHARMA diagnostics. However, there don't seem to be a lot of help online on how to interpret the results. Does ...
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1answer
23 views

Statistical specification for a Regression with continuous finite range count like data

I am interested in explaining what kind of personal characteristics and work environment variables are associated with sickness absenteeism. My dependent variable is the total number of days a given ...
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Is my data inappropriate for a zero-inflated regression model?

I am working with count data where I have an abundance of zeros for one of my categorical factors (Day). I have generated two models, p1 and m1, with zeroinfl() and ...
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1answer
49 views

Zero-inflated model predicting only a small range of values. I need help

I built a ZI model and it is producing predicted values that are from a very small range when compared to the observed values. Plus it does not produce any zeros. See the fitted vs. observed graph ...
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34 views

Variable importance when performing zero-inflated Poisson regression in R?

In short, I need to get the importance of the variables after a zero-inflated regression, with all my predictors being dichotomous factors. I tried something like this: ...
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Yes/no GZLMM zero inflated

I have got a variable which I want to analyse using a GZLMM with binomial distribution as the variable is coded as yes/no(1/0). However, there are a lot of zeros and not many 1's.I was hoping to ...
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1answer
19 views

What coefficients to include in logit component of zero-inflated and hurdle models?

I'm new to statistics so hoping for a ELI5 explanation! I need to use a hurdle (or zero-inflated) model to try and replicate someone elses methodology on a newer dataset for my undergraduate ...
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1answer
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My data has overdispersion but the Hurdle model estimated theta is 0. What am I doing wrong?

I am confused by the dispersion parameter from my model. My data fails the overdispersion test. It's mean is 28.7, the variance is 18655.27. N=2916 of which 32% are zeros. How can theta equal 0 in ...
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2answers
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Different significance found in zero-inflated negative binomial vs. binomial logistic regression

I'm having a hard time reconciling two seemingly contradictory findings: In a binomial logistic regression (where 0 is abstinent and 1 is relapsed), the 7 category nominal predictor showed ...
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205 views

GLM Frequency and Severity Models. How Do I improve from here? (R code) [closed]

Background: I've been tasked with creating a rating model by Peril using GLMs. It's commercial lines property, so the data is pretty sparse. The carriers have been asking for Premiums by peril, so we'...
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1answer
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Zero-inflated vs not Zero-inflated models for count data

I am analyzing a small dataset (d) of urinary track infections in a group of residents of a long-term care institution over a period of 6 months. The total number of patients was 29. I had used ...
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1answer
67 views

Handling quasi-perfect separation in a zero-inflated negative binomial regression in R

I want to run a zero-inflated negative binomial regression in R, but one of my variables exhibits quasi-complete separation and throws errors for both the negative binomial and logistic pieces. I've ...
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1answer
78 views

Using gamm4 on zero-inflated count data with Tweedie or zero-inflated Poisson distributions

I'm working with a dataset with a large number of zero-counts on the response variable. This dataset consists of qualitatively coded interviews in a number of important categories, but many of the ...
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2answers
111 views

GLMMs for count data with glmmTMB: random slopes specification, cross-level-interaction and strange results

folks, I recently found the great glmmTMB package which I hoped would help me with my models. My data are 60,000 facebook posts that are nested in 51 companies (i.e., the posts by these companies). ...
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140 views

General linear mixed model in R which will fit quasi family [closed]

I am trying to run a GLMM with a quasibinomial family (my data is 0 inflated and I have a negative min x value), but am receiving this error message as quasi families cannot be used in glmer: ...
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1answer
120 views

Trouble modeling zero-inflated data. Estimates and standard errors are off with GLM, GLMM, and ZI models

I conducted a study looking at the attraction of different species of insects to 5 different chemical treatments (I have had other issues with this dataset explored here and here). This experiment ...
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Zero-Inflated Rare Keyword Impact Prediction

Suppose we have a dataset $X$ of features and a target binary prediction $y\in\{0,1\}$ for each datapoint. Each row of $X$ consists of counts (a bag of features). We can normalize each row of $X$ to ...
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Compare two samples with many zeros

We carried out a number of some experiments and got 10 independent 2-samples datasets. Is it possible to show a significant difference between the two samples, if each of them contains more than 75% ...
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What statistics can I use?

I have done a research looking at different frequencies of abrasions (ablation, etc.) over time (in hrs) and my data mainly consists of zeros. As I am weak in statistics, I am unsure which statistics, ...
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1answer
137 views

Mixed effect zero inflated negative binomial model: “the leading minor of order 1 is not positive definite”

I am having trouble fitting a mixed effect zero inflated negative binomial model to my data using the GLMMadaptive package: ...
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1answer
831 views

Modelling and interpreting brms output

I do apologize in advance for this might be very basic questions. I am not really familiar with Bayesian statistics and too, unfortunately, this is the very first time I am analysing data in general. ...
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Do zero-inflated models induce selection bias?

Zero-inflated models (e.g., ZI poisson, ZI negative binomial, hurdle) assume two processes for the generation of the observed outcome variable: a process for deciding whether the outcome is zero or ...
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1answer
242 views

R: GLMM for unbalanced zero-inflated data (glmmTMB)

Study design: I have count data of snails per date, counted over many dates at sites, nested in localities. So, in each locality the snail counts come from several different sites, repeatedly ...
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Independent variables with an important share of zeros

In a linear panel data model, is it an issue to have explanatory variables with an important share of zeros (e.g. 40% of observations are zeros)? Can the coefficients of an OLS regression be biased?