# 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.

769 questions
Filter by
Sorted by
Tagged with
1answer
17 views

### Interpreting large coefficient values in Poisson regression

I'm running a Poisson regression using proc glimmix (log link) with the outcome of count of events in each month and an explanatory variable. The explanatory variable has a coefficient value of 3.3. ...
0answers
14 views

### Different regression models in one research project?

I'm working on a research project on alcohol behaviours where I am looking at 2 outcomes: 1) number of drinks; 2) preference (5-point Likert scale, ordinal). There are two things I'm confused about: A)...
1answer
26 views

### Is a signficiant interaction term in Poisson really statistically significant?

I am very aware that the magnitude of the interaction effect in nonlinear models does not equal the marginal effect of the interaction term, can be of opposite sign, and its statistical significance ...
0answers
23 views

### Help in understanding the raw data behind a Poisson regression and its log transformation [closed]

I would appreciate a sanity question. I have two questions concerning my count data: Question 1 I've just finished reading this article: https://www.theanalysisfactor.com/regression-models-for-count-...
0answers
27 views

### For counting participants should I use linear regression or poisson regression?

I would be very grateful if anyone with a stats background might sanity checks whether my approach is correct. I am recording the prescribing of a particular drug over time. Ultimately, beyond the ...
0answers
10 views

### Different p-values in Repeated Measures Poisson Regression and Type3 Analysis

I am working on data for 10 years that has counts of hospitalization and population size by countries. I also have other covariates that I need to control for. Using GEE Poisson regression, and ...
0answers
13 views

### Poisson vs ordinal logistic regression for “number of times” outcome

I have two outcome variables: A) 5-point Likert scale B) the number of drinks a participant had (ranges from 0-5) My independent variables are sex, age, income, location, and ethnicity. I'm planning ...
1answer
29 views

### Is the residual deviance / residual dof equivalent to reduced Chi^2?

Question: I'm using a poisson fit; is the residual deviance = $\chi^{2}$, and residual deviance / residual degrees of freedom = $\chi^{2}_{reduced}$? Does this method provide a valid tool comparable ...
1answer
23 views

### Log and exponential uncertainty propogation

I am processing data on a radioactive decay experiment, and need to find the errors on some quantities that I can get from some fit parameters. I would like to obtain: $\sigma A$ from $A = e^{a}$, ...
0answers
12 views

### Data visualisation and exploration for count data

I have a fairly large data set with ~1000 observations about residents of an area. This is a dataset consisting of 15 variables, of various types (eg age, sex, income, years spent living in the area ...
1answer
28 views

### Am I misunderstanding Zou's method for computing relative risk for binary outcomes using Poisson regression?

It seems that relative risk estimation using Poisson regression is a popular approach in epidemiology, with a couple of papers I have recently looked at (for example  and many others like it) ...
0answers
23 views

### Extracting an interpreting Poisson regression coefficents [closed]

I am currently running a Poisson regression that aims to model the following formula: $S_{ij} = A_i O_i W_j^\gamma exp (-\beta d_{ij})$ Where $S_ij$ is the target variable, $A_i$ and $O_i$ are given ...
0answers
9 views

### Poisson Regression assumption of constant rate in a fixed interval

My understanding of the Poisson distribution is that the probability of an occurrence is the same for any two intervals of equal length, or of equal space if not in a time dimension. My confusion is ...
1answer
19 views

### How to interpret poission regression coefficients?

I am given the following problem: Suppose that we observe $n$ independent count outcomes, where $n/2$ are from class 0, coded as $0$, and $n/2$ are from class 1, coded with $1$. The sample mean of ...
0answers
6 views

### Why can negative binomial regression be used to model event rate/count data

It seems negative binomial regression can be used interchangeably with Poisson regression to model event rate? but I don't understand how it works. Poisson distribution is for count data. Poisson ...
1answer
46 views

### Help with Poisson regression accounting for repeated measures

I'm not a statistician, but need to use these clever tools to analyse some data I have. I have a really simple dataset to analyze (see below. cases=disease counts, pop=total number of subjects sampled ...
0answers
38 views

### Quasi-Poisson Regression with non-integer count data

I am trying to run a fixed-effects Poisson Quasi Maximum Likelihood estimator on 3-dimensional(year, country, industry) unbalanced Panel data. The dependent variable is the number of patents(non-...
0answers
4 views

### Poisson regression for volume/time of parts delivery?

I've been reading through Statistical Rethinking and I'm not sure that I get when Poisson regression is appropriate (as opposed to linear regression or simple poisson distribution parameter estimation....
0answers
20 views

### Intuition for reasoning between Quasi-poisson and Negative Binomial regression

I am aware of the several similar questions existing here (like this, this or this), but my question is slightly different and remains after going through most of those posts. Specifically, my ...
0answers
15 views

### Modelling underdispersed poisson distribution for count data

I am currently trying to model the count of agent in a system, in which I systematically varied the available space. I figured that I could use a classical Poisson distribution. However, the model is ...
0answers
12 views

### poisson regression or multiple linear regression for predicting number of times an item is sold

I am working on a problem to identify the features that are driving the number of times an item is sold. I have about 900 similar items and about 8 variables. I also need some much each coefficient is ...
0answers
32 views

### Autocorrelation in Poisson model's residuals - Is my model not specified correctly?

I am fitting a poisson regression model in R to count time series data to perform an Interrupted Time Series Analysis, the aim of my analysis is to see if an intervention affected the counts. I am ...
1answer
40 views

### How to handle a constant parameter in a Poisson regression?

I have a Poisson regression model with rate, $\lambda$, defined as $ln (\lambda) = \alpha + \beta + \gamma$. Here $\alpha$ and $\beta$ change and $\gamma$ is 0.5 for each observation. $\gamma$ is ...
0answers
56 views

### Fixed-effects Poisson estimator using quasi-maximum likelihood

I am trying to run a fixed-effects Poisson Quasi Maximum Likelihood estimator on 3-dimensional(year, country, industry) Panel data. The dependent variable is the number of patents(non-negative and non-...
0answers
16 views

### Can you compare AIC to WAIC?

This may be a simple question, but I'm at a bit of a loss. Can I compare AIC to WAIC for the same model, one estimated using general linear models and one using Bayesian estimation? Or do I need to ...
0answers
26 views

### Which Regression to use including Code in R

I am trying to predict a proportion take up rate. My dependant variable is between 0 and 10, meaning 0 and 10% have taken it up. So it is not entirely continuous because it stops at 10 it doesn't go ...
0answers
12 views

### Interpreting a generalised linear mixed model and missing values. Plus what dose the Intercept say?

I am working on my data and i have 3 bordering element types, 4 distances and 18 different LS (locations). I would like to do a GLMM, with bordering element types + distance and their interaction with ...
1answer
56 views

### how to fit four parameter logistic regression (poisson) R?

I'm trying to fit a four parameter logistic regression to model bird species richness (Patch_Richness) in response to forest cover (FOREST500). I need to add km as a co-variable to the model (km= ...
1answer
24 views

### using Poisson or gaussian when modelling income

Simplified scenario. I want to model income depending on gender and education. I have to possibility using glms: ...
2answers
28 views

### Fitting a Poisson GLM with level 1 and level 2 predictors

I'm trying to fit a GLMER poisson model with level 1 and level 2 predictors. There's plenty of information in this website about fitting a Poisson GLM with level 1 predictors. My question is whether ...
1answer
73 views

### R: How does GLM deal with zeros in Poisson regresion?

How are zeros passed into Poisson regresion? I mean the log of 0 is -infinity, so it shouldn't be able to provide zero counts as the dependent variable. Does it use some kind of analytic technique to ...
0answers
29 views

### Why are we entitled to use the link function we prefer the most?

For a project, we have been trying to fit different models. When we used a Poisson regression, so a glm with a Poisson family, initially our fit was quite bad. But once we used the identity link ...
0answers
17 views

### Pseudo R squared for the negative binomial regression

I am confused with the Pseudo $R^2$ computation of the negative binomial regression model. For the logistic regression, we can compute the Pseudo $R^2$ as ...
0answers
10 views

### How to use Hausman Taylor instrumental variables estimator for Poisson Regression

I have a panel data. The dependent variable is a count variable, so a Poisson regression is more appropriate than a linear regression. I am aware how to use xtpoisson and xthtaylor. But xtpoisson does ...
0answers
14 views

### Exposure or Independent Variable in count models?

I am fitting count models to test hypotheses and compute association strength (not interested in predictions). Each observation is a small hexagon part of a geographic tessellation of some country of ...
0answers
10 views

### regression by grouping the dependent variable

I have a large dataset exploring the effects of the independent variables on the dependent variable using Poisson regression since the dependent variable is a count variable. However, the range of the ...
1answer
54 views

### Why is my gaussian GLM better than my poisson GLM for count data?

Given the following code: ...
0answers
4 views

### Interpretation of quasi poisson regression with offset

I am trying to find out how to correctly interpret the coefficients for a poisson regression. My main outcome of interest is the number of antibiotics prescribed (count) or the rate of antibiotics ...
0answers
10 views

### Interpret the DHARMA simulation for the negative binomial regression

Our response variable is highly skewed and there is evidence of overdispersion as well. We used $pseudo R-squared$ and simulation using the DHARMA package to assess the quality of the model fit. How ...
0answers
29 views

### choice of using poisson or logistic regression for rates? Which is better and how to check?

Suppose I have weekly aggregated data, spread over 10 weeks, and I want to run a regression model on the weekly percent of a certain outcome (i.e. I do not have individual observations). For example ...
0answers
20 views

### Understanding the output of Poisson Regression

Is there a way to calculate the mean additive effect for an independent variable on a dependent variable, where the dependent variable is a discrete counting variable? This would be similar to the ...
0answers
5 views

### Sum of $n$ relative risk ratios and Poisson regression

Consider $n$ joint PMF defined by two Bernoulli r.v. $X_i$ and $Y$. The probability $P(X_i, Y)$ is estimated as: \begin{array}{c|cc} & Y = 1 & Y = 0 \\ \hline X_i = 1 & \frac{a_i}{a_i + ...
0answers
66 views

### Evaluate the quality of the negative binomial regression model fit

Our response variable is highly skewed and there is evidence of overdispersion as well. We tried with the Poisson, and Quasi-Poisson models. Both Poisson and Quasi-Poisson models failed to satisfy ...
0answers
137 views

### Appropriate goodness-of-fit test for the negative binomial regression

I have used the following Pearson $χ2$ test and the deviance test to assess the negative binomial regression using R as ######################################### ...
0answers
28 views

### Poisson/NB regression with lags on Time Series data

I'm trying to put together a prediction tool for counting time series data. My idea is to go with a lagged Poisson/Negative Binomial regression model. However, I'm uncertain about a many things. Is ...
0answers
5 views

### Interpreting continuous explanatory variable in Poisson rate regression with offset term?

There are several excellent questions and answers on Poisson regression hosted by CrossValidated. I have consulted extensively with these, for example: When to use an offset in a Poisson regression? ...
2answers
52 views

### Multiple Poisson regression (?) in R

My data consists of 1 dependent variable and 4 independent variables, all the IV's are continuous. Some of my data is presented below to give an idea of how it is structured. The dependent variable is ...
1answer
50 views

### Regression with percentage (%race/gender) as a predictor variable

I have data on hospital admission rates for 5 years at zip code level. I also have percentages on each of the 3 race categories, and percentages of gender for each of the 5 years at the zip code ...
1answer
65 views

### Poisson regression or ANOVA, repeated measures or independent?

I have been trying to figure out the best way to approach analysis of my data for a while now and I'm struggling to understand if a Poisson regression is correct and, embarrassingly, I'm not sure if ...
1answer
75 views

### Poisson regression with strictly positive CONTINUOUS dependent variable

A bit of a background to my questions: I'm coming from the field of strategic management, and the prevalent technique is large sample analysis is fixed-effects or random-effects regression whenever ...