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).

Filter by
Sorted by
Tagged with
5
votes
1answer
24 views

Interpreting random effects in zero-inflated models

For context, I have a longitudinal study measuring counts of bacterial sequences in human stool collected during a dietary intervention. Initially, I was going model the change in each bacterium (...
1
vote
0answers
24 views

Zero inflated and hurdle models - is it common do 'build your own' with e.g. ensemble model?

I have been given a new analytics problem to solve. The context is app analytics where we would like to predict total revenue per app install after 30 days from install based on just 7 days of data. I....
0
votes
0answers
8 views

Interpreting Zero-Inflated Negative Binomial Residual Diagnostic Plots [closed]

I have built an associative model using zero-inflated negative binomial in SAS using proc genmod. I am new to this regression method, and I have significant estimators for both the count model and the ...
0
votes
2answers
61 views

One group has only zero values, should I use parametric or non-parametric test?

I have 3 groups (n=5 per group) from biological data. I have checked the normality of my groups using the Shapiro-Wilk test and two of my groups are normally distributed. However, the 3rd group values ...
3
votes
0answers
46 views

How to deal with zero-inflated proportional data in GLMM?

I have proportional data, i.e. number of individuals out of 6 that choose a certain option in a multiple choice experiment, so there are just 7 possible outcomes for each option: 0/6; 1/6; 2/6; 3/6; 4/...
1
vote
1answer
138 views

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'...
1
vote
0answers
40 views

Multivariate zero_one_inflated_beta regression

I want to run a zero_one_inflated_beta regression with brms on the following multivariate formula: ...
1
vote
0answers
12 views

Handling large percentage of zero-valued observations in a continuous dependent variable in a panel dataset

I am writing a paper using a panel dataset in which my depepent variable is continuous has an large percentage amount of zero values observations. Those zero values are real zeros, I mean they are not ...
0
votes
1answer
176 views

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 ...
1
vote
1answer
527 views

GAMM with Zero-Inflated Negative Binomial - Looking for a package on R

I am looking for an R package to fit Generalized Additive Mixed Models with ZINB distribution, as ZINB is not available in the mgcv package nor in the gamm4 package. I read here that it might be ...
0
votes
1answer
48 views

Statistical tests for count data with many zeros

I have to compare three groups (each group is a customer to a subscription box company). Group A received treatment A. Group B received treatment B. Group C received no treatment. We count the ...
0
votes
0answers
52 views

JAGS code for Poisson or negative binomial hurdle (zero-altered) model with autoregressive residual

I am using Bayesian zero-altered Poisson and negative binomial models analyzing time-series data with JAGS. Because the ACF of the Pearson residuals showed autocorrelation, I decided to apply ...
0
votes
0answers
24 views

Unusual residual artefacts in GLMM, is GAM or another model more appropriate?

I'm having trouble finding an appropriate model for my data. The data comprises behavioural observations of chimpanzees, where I instantaneously sampled their locomotor behaviours and parameters of ...
1
vote
0answers
97 views

Interpretation of zero-one-inflated beta models in brms

I have 20 participants who have watched 18 clips. Every clip belongs to one category of pleasure (p_cat: negative, neutral, positive) and one category of intensity (i_cat: low, medium, high). I have 2 ...
0
votes
1answer
305 views

How to fit Anomaly Detection model to imbalanced time series data(Zero Inflected time series data)?

I'm doing a predictive modeling for predicting anomalies in the sensors data. For this I'm using the twitter AnomalyDetection package in R. We are getting ton of data from sensors for every day. For ...
1
vote
1answer
145 views

Compute a measure of explained variance for hurdle models in R

I am working with a dataset df which comprises count data count and a number of categorical variables. ...
1
vote
1answer
21 views

How to analyze data with unequal length of observations and many zeros?

I want to analyze the impact of the rain on smoking probability. I observed people in two cities on the streets and marked the following parameters: city, gender of the person, duration of observing ...
0
votes
0answers
40 views

Extracting the right summary statistics from zero-inflated data sets (i.e. a sparse matrix where everything non-zero is a statistical outlier)

I'm a consumer tech startup founder with rudimentary background in statistics. I need help in processing a large, sparse matrix. I'm logging all actions users are undertaking in my app. I then ...
2
votes
1answer
142 views

Hierachical cluster analysis of ordinal variables?

I have a dataset containing 400 variables (chemical compounds, amount classes) with values 0,1,2, or 3 and 50 entries (species). Can I use hierarchical cluster analysis to get a dendrogram that ...
0
votes
0answers
14 views

How to obtain different values of “parameter k” in a mixed-effects negative binomial model?

I have a dataset with two level factors - fertilizers ("Nitrogen" or "Phosphorous") that differed in their concentration level("...
2
votes
1answer
40 views

Poisson on frequency data with many 0, underestimated output

I have got a frequency table of how many events occur within a 5-minute time window. ...
4
votes
0answers
463 views

How to write unnormalized posterior when prior is a mixture of continuous and discrete

Suppose I want to do bayesian inference on the regression problem $\beta$ for Y = X$\beta$ + $\epsilon$ for $\epsilon_i \sim N(0,\sigma^2)$. The complication is that the prior for each component $\...
1
vote
1answer
42 views

Inferences from a zero-inflated negative binomial distribution?

Frogs are generally known to spatially aggregate during egg-laying. I manipulated their egg-laying sites with different fertilizers ("Nitrogen" or "Phosphorous") that differed in their concentration ("...
1
vote
1answer
55 views

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 ...
0
votes
0answers
18 views

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 ...
0
votes
2answers
3k views

Data transformation to fit gamma distribution in R

I'm having trouble to fit and simulate a gamma distribution using the fitdistr function from the ...
3
votes
3answers
253 views

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% ...
0
votes
0answers
21 views

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 ...
2
votes
0answers
67 views

Two sample test clustered data, continuous variable with zeros

I have a situation where an experiment is being run in the following manner: A one stage cluster sampling (I think this is accurate description) is conducted whereby there are multiple organizations ...
3
votes
1answer
53 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 ...
1
vote
0answers
189 views

Test means of populations with lots of zeros, is sampling the way to go?

I am trying to test whether means of two populations with lots of zeros are different. Here is the following python code example: ...
3
votes
1answer
138 views

Classification followed by regression?

I have the following problem: I have a dataset for which my observations have a bunch of features and a continuous response (regression problem). However, some of my observations (about a fourth of ...
1
vote
1answer
528 views

Correlations in count data with many zeros

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 ...
1
vote
1answer
17 views

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 ...
1
vote
1answer
470 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 ...
1
vote
1answer
180 views

What approach can I use to analyse zero-inflated, overdispersed, count data with very low replicates and a nested random effect?

I am having trouble with analysing some of my data. I'm trying to test the effect of a treatment with two levels (Treatment/Control) on the abundance of ants belonging to different dominance ...
0
votes
1answer
113 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 ...
1
vote
0answers
59 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 ...
3
votes
1answer
163 views

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 ...
2
votes
1answer
106 views

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 ...
0
votes
0answers
33 views

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 ...
2
votes
0answers
63 views

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 ...
1
vote
1answer
69 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 ...
0
votes
1answer
28 views

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 ...
3
votes
1answer
52 views

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 ...
0
votes
0answers
23 views

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 ...
0
votes
1answer
50 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 ...
0
votes
0answers
9 views

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 ...
1
vote
1answer
71 views

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?
3
votes
1answer
62 views

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 ...