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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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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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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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Zero-inflated model-Nans [closed]

I am running a zero-inflated model in R. The estimation results show value "NA" for the standard errors, and I am receiving this message "Warning message: In sqrt(diag(object@vcov)) : NaNs produced". ...
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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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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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How to interpret zero-inflated regressions? [duplicate]

Any resources for understanding how to interpret a zero-inflated negative binomial regression model? Specifically, I'm using r
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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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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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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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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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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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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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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
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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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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
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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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1answer
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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
105 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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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
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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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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?
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Distribution/analysis method for small dataset with many small/zero values

I have a relatively small dataset (160 observations), of which a very large number of values for response variables are zero or very small (e.g., 114/160 values are 0; range 0-4250, with only 11 ...
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Model for semicontinuous data with structural and sampling (true and false) zeros

I am dealing with a very hard-to-work data set: fish larval density. It is a semicontinuous data, with 90% of zeros and a right-skewed distribution, with few very large values. One problem is that ...
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1answer
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Residuals still zero inflated after running zero-inflated poisson mixed effect model with glmmTMB

I am working with observational data which has a right skew in the dependent variable. This is a mixed effect model with a poisson distribution as based on discrete data. After finding the residuals ...
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Contradiction between zero-inflated poisson model coefficients and graph of the model?

EDIT: Added an reproducible example For one of my models, it seems the coefficients and the graphed out model do not agree. I'm working with adverse effects data, in which intense reactions are rare ...
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Calculate interaction effect confidence intervals in zero-inflated poisson regression

I'm conducting a zero-inflated Poisson regression using the pscl package in R. I've included interaction terms but am having an issue with interpretation. I am assuming an additive effect and summing ...
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1answer
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Distribution to use in a regression with a positive skewed variable with many zeros (homicide rates)

I want to study the determinants of homicide rates. However, I see when exploring the data that my dependent variable (homicide rates) has many zeros and is positive skewed. Which distribution family /...
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Hurdle Model: Identify Distribution for Second Stage

I have two kinds of dependent variables, both count data. The first one is binary, and the second one an ordinal index based on multiple binary variables (sum). As they are based on coded occurrences ...
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1answer
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Dependent variable with many zeros in a difference-in-differences model

There is a question with a similar title: How do I estimate a differences in differences model when the dependent variable has many zeros? However, mine is a little different. Let's assume I have a ...
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1answer
107 views

Regression predictions show far less variance than expected

New to R and fairly new to statistics - appreciate any input. In short, I'm trying to develop a predictive regression model but after fitting the model on training data, the output for my testing ...
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1answer
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Update a zero-inflated Poisson model to adjust model predictions

I am trying to model out how a clinical metric declines over time with various therapies. I'm a bit new to R and statistics, so appreciate the patience and help. I have two data sets - the first a ...
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1answer
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Zero-inflation GLMMs: On the use of different sets of explanatory variables in main and ZI formulas

my questions are general in nature so I won't provide any data. For reference: I am using the package glmmTMB in R so if my terminology is weird it is because it is a mix of this and other sources I'...