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Questions tagged [poisson-regression]

Poisson regression is one of a number of regression models for dependent variables that are counts (non-negative integers). A more general model is negative binomial regression. Both have numerous variants.

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What model should I use if I want to describe the relationship between the % and binary outcome

I want to model a relationship between the % of students who received a flu vaccine at a certain school and whether their school had a flu outbreak or not. Thanks
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G*Power and simulation produce very different sample size estimates for a Poisson regression

I've been attempting to conduct a sample size calculation for a Poisson regression. G*Power produced a sample size of 472. Parameters for G*Power Tails = 2 Exp(B1) = 1.233 alpha = 0.05 Power = 0....
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Proof that a poisson regression with 2 categorical predictors is the same as each observed mean

I have a poisson regression with 2 categorical predictors to predict\estimate the sales of product $p_i$ on location $j$: $\hat{X}_j(p_i) = e^{\gamma_0 + \alpha_i + \beta_j + \mu_{i,j}}$ It appears ...
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Quasipoisson model variable selection and find best model

I am running a Quasipoisson model in R with a lot of variables. This is my outcome: I want to find out which variables have an influence on the dormouse abundance (number of nests). After doing the ...
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Confidence intervals for survey-weighted Poisson regression in R where counts are totals of the survey weights

Forgive me if this is a very basic question. I am using a large database of healthcare encounters that uses a stratified sampling approach. Each row in the database is a sampled encounter, and has a ...
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How to establish the effects of a competitor near my store location?

As part of my studies of statistics, market analysis and data analysis, I’m facing the following problem but not sure if the answer I’m proposing it is correct or not. A commercial retail store with “...
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Poisson bias adjustment

So I was hoping someone could help me make sense of this problem. I came across this paper that discusses how the FSL probabilistic DTT may yield bias tractography relating to the physical distances ...
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Statistical adjustment for regression

I already checked out the answer to this: enter link description here It is not a duplicate and that did not answer my question. I wanted to try to ask a different question regarding a similar ...
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Poisson log linear Regression: using either R or python

I was hoping someone can help me with this problem. I posted a similar question earlier but it's not the same. I have the following: A 2x2 matrix of structural connectivity values between brain ...
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Poisson residuals

I have been working with count data (n=66) recently, trying to fit a simple model to explain distribution in an outcome whereby the count (number of successful trials in a region) is relative to an ...
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Correcting data using poisson-regression

I'm new to stats and I was wondering if anyone had any good resources that could explain to me: How one can correct their data (false-positives) using Poisson-regression. I've been looking for some ...
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PROC GENMOD Negative Binomial doesn't predict zeros

I am using PROC GENMOD with time series data, I have tried to work with Negative Binomial, Poisson, GEE and Zero Inflated Poisson, but in each case when I score my validation dataset, I am getting ...
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How are distributions and regression models related?

This is likely a very simple question for many of you but is something that has been poorly covered in the statistics courses I've taken to date. We have talked extensively about distributions (normal,...
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GLM and implementation of Poisson regression model in R by hand

first of, this is not my school exercise but a given example that I'd like to convert from Stan to my own code. I am very much a pragmatic learner so doing this helps me a lot to visualize the problem....
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Spatial Poisson model correlation structure

I'll preface this by saying I'm VERY new to this spatial epidemiology world. I'm running a spatial poisson model and have set its correlation structure as exponential. However once I arrived at my ...
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Would it be more appropriate to use negative Binomial regression instead of Poisson regression if my sample variance is greater than my sample mean?

My response variable $y_i$ denotes the number of articles produced by journalist $i$ in the last two years. It is a count variable with fixed exposure hence why I chose to use Poisson regression. I ...
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Model Change In Incidents Using Three Cohorts

I am working with 6 waves of survey data that represent three different birth cohorts. My outcome is diabetes. Specifically I want to examine trends in the risk of diabetes (incidents). I have read ...
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Pooling estimates and variances with zero counts

I have a dataset with 10 different sampling groups. The sampling is done in order to maximize the ability to find events. The sample looks a little like: ...
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Population Mean Estimation using Poisson Regression?

Assuming I have count data, where x is the counted variable of interest and y is some total number of counts for a given sample. Then, can I improve my estimate of $\mu_x$ by using a Poisson ...
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Modeling rates with complex survey data

I have data derived from a stratified, cluster random sample with post-stratification weights (corresponding to the inverse probability of response). These are person-level data. Let's say I want to ...
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count data and Poisson GLMs to predict monetary amounts

I have to predict money amounts, which are always greater than 0. The distribution is very tailed (i.e. there are many small values but also many large data). Just wondering would a count data model ...
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How to write the Poisson regression formula in both proper and understandable way for animals scientists

I analyze the following count data gathered in a contingency table using Poisson regression with the formula given below. Category Group C1 C2 C3 I 4 1 3 II ...
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Poisson regression on a contingency table - overdispersion

I have the following contingency table Category Group C1 C2 C3 C4 C5 Total I 4 1 3 9 9 26 II 7 7 1 6 5 26 III 0 2 1 1 13 17 IV ...
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Can I use rates (e.g., crude rates) as an explanatory variable (covariate) in regression?

I am working on formulating a regression problem where my dependent variable is the number of heart disease cases (count data) in a population. I am looking to do an ecological poisson-based ...
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Long tailed count probability distributions - with available likelihood calculation and random number generation

in real world data, often (always to me) happen that for modelling count data Poisson Negative binomial multinomial dirichlet-multinomial probability distribution, are not robust to outliers, as ...
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can i use random forest for feature selection and then use poisson regression for model fitting? [duplicate]

Variables that are important in random forest don't necessarily have any sort of relationship with the outcome. So would it be wise to use random forest to gather the most important features and then ...
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Why does a summary() call on a GLM model give me T rather than F values?

I constructed a quasi-Poisson model ("mod") with two predictors and an interaction term using glm(). One of the predictors is ...
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How to compare model fit of OLS and Poisson regression?

I have built two regression models to predict sales of different products based on a number of explanatory variables, with an offset term for the number of days each product was on sale. One is a ...
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How to use Poisson regression in R to determine if two different years of count data are statistically significantly different?

I’ve been asked to determine whether two years of count data (before intervention and after intervention) are significantly different using Poisson regression in R. Any suggestions?
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ANOVA tables are exactly the same using OLS and Poisson regression?

I have fit two models in R, as follows: m1 = lm(y ~ x * z) m2 = glm(y ~ x * z, family="poisson") Where y is the dependent ...
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Zero-inflated count data simulation in R

I need to simulate data to explore the question: "What happens if my data have zero inflation, but I ignore it and fit a standard count model instead?" More specifically, how can I add zeros in a way ...
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Negative estimated means in Poisson regression output

Can anybody help me understand what the negative estimated means in a Poisson regression mean? I am trying to model the count of damages during transit for 4 different logistics providers. To make it ...
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Time taken to receive funding: A count variable?

I am trying to predict time taken by a startup to receive funding based on specific characteristics of entrepreneur. Regardless of a bunch of transformations and ...
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How can I (visually) diagnose the residuals of a quasipoisson regression?

I've estimated a quasi-Poisson regression in R - a choice I've largely opted for because it "makes sense" for my application - I'm looking at count data with lots of zeros in the response variable, ...
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How to interpret Zero-Inflated Poisson in WINBUGS?

I have Winbugs code for a zero-inflated Poisson (ZIP) model. I obtained this code from my lab at university and the person who wrote it is not accessible for me to ask questions. Here is the code: <...
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VGAM plotting predictions and confidence intervals genpoisson/generalized poisson

I fit a generalized poisson using VGAM and can output predictions using predict. However, the fitted.values are a matrix, ...
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Is there a option to find studentized deleted residual for Zero Inflated Poisson model?

I have fitted my 3x3 contingency table with Zero Inflated Poisson model. I am trying to explore all types of residuals associated with the model. There is no option to calculate studentized residuals. ...
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Deviance residuals in Poisson GLM

I am learning the concept of residuals in modelling. I performed a Poisson GLM for a 3x3 contingency table and I got the summary of the model. My question is: the deviance residual from the in-built ...
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Is Poisson model in R appropriate here?

I am graphing a dataset in R that is whether a customer makes an unplanned purchase which can take values from 0-infinity, against customer path length which may take only positive values. The ...
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Use of cross-sectional survey weights when employing mixed-effect regression models using multiple cross-sectional data

I have conducted an analysis using multiple-cross sectional datasets (i.e. combining different waves of the same survey). The survey provides cross-sectional weights for each wave. Considering that a ...
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Negative binomial model vs zero-inflated negative binomial - theoretical justifications

I have a count variable that I would like to predict using a categorical variable (it has 4 levels). I would like to decide whether I should use Poisson, negative binomial, or zero-inflated negative ...
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Adding a predictor reduce R squared

Currently, I am doing Poisson models with N=16,000. My study requires me to find $R^2$ for each model (using 'rsq' package). When I add P12, the $R^2$ decreased as shown below. ...
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Zero-inflated Poisson with clustered data in R

I am working with ecology count data with a significant amount of zeroes, and I used a multivariate zero-inflated Poisson regression to evaluate the impact of two independent variables on my dependent ...
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Poisson assumptions

I am dealing with a dependent variable that is either 0, 1 or 2 in theory it is unbounded and it can take values more than 2 so I am motivated to test Poisson model first. The frequency counts for ...
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Can covariance parameter estimates and fixed effect estimates of a Generalized Linear Mixed Model be correlated?

Specifically, I am fitting a Poisson Mixed Model with random coefficients and intercepts on longitudinal count data. The rate ratio between time points is log normal with expected value $e^{\mu}e^{\...
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Poisson data prediction with month variable

I have count data based on the number of failures per month. I have month, year, type of failure, and the count of fails. I have tried using R's glm package, ...
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Performance of a product on an unknown location

The problem I aim to solve is to find the right location in a shop for each product. The shop is a retailshop, not a supermarket. I have 32 weeks of salesdata of products on shelves within a store (...
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Mixed models for zero-inflated count data in R?

I have a dataset containing scores on a measure of uncommon experiences. The scores are derived as a count of the number of items rated as present divided by the number of items that were answered by ...
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Interpreting summary output from poisson glm in R

I'm learning about regression at university and I really strugging to find good sources to understand the process of model analysis. I have this model below. I'm trying to make the best fitting model ...