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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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Centering / standardizing leads to very different results for GLM (logistic, poisson, negative binomial distribution)

I have a dataset with count data and around 1 million observations. My regressions contain around 40 variables (binary and continuous) and 10 thousand fixed effects. I analyze this dataset with linear,...
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Why does pglm give different results thans log-plm?

I'm looking to regress a fixed-effects model on count data. My initial approach was to take the log of regressor on R's plm package. Then I found out about the pglm package, which enables general ...
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Poisson regression with continuous data

I have a time series of floating numbers, say, 0.1, 0.5, 1.1, 0.6, 2.0, 1.4, 0.4 Now, I would like to model this series with Poisson regression, since the numbers, even though they seem ...
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mixed effect model?

I have 365 days of bike sharing demand data for 15 stations. I am thinking of taking each day data as a data point (n=365*15=5475) and relate daily weather variable as well as land use variable. The ...
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Formula for deviance residuals for Poisson model with identity link function?

I understand the deviance residuals $r_D$ for a Poisson GLM with log link function are given by $r_D = \mu_{ij} \log(\mu_{ij}/\hat{\mu}_{ij}) + (\hat{\mu}_{ij} - \mu_{ij})$ I was wondering though ...
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Poisson Regression vs. Exponential_Weibull vs. Cox Regression vs. Negative Binomial

Problem: I would like to predict the number of days a student continues with school using student and school level covariates (no censor data). Data includes the number of days that the student ...
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How do you stratify a Poisson regression in GLM?

I would like to obtain a stratified baseline hazard in a Poisson regression model. What is the correct way to do it ? Let A (=0/1) be the binary covariate on which I wish to stratify my baseline ...
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POISSON REGRESSION AND OFFSET VARIABLE

I am using a Poisson regression model with a count data. More specifically, my dependent variable is the number of children dead. My feeling is that I could use a Poisson model with an offset ...
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Interpretation of Conway Maxwell Poisson regression coefficients

For a simple Poisson regression, I would interpret the coefficient as (1-exp(coef))*100 for percentage change in y given a unit change in x So for a Conway-Maxwell Poisson regression, Sellers and ...
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Modeling daily purchase events / website traffic, time series or independent events?

I've been thinking about how best to model sequential events like purchases on a website, or website traffic. I'm curious if people think this is best modeled as a poisson process (or something like ...
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Visualising Generalised linear models

I read about linear regression where we assume, the response is linear and the noise $\epsilon$, follows $N(0, \sigma^2)$ (Gaussian noise model), this leads us to conclude $E[Y|X] = b^*x$ and that the ...
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How do I model count data (Poisson regression) that has a seasonal pattern?

I'm rather new to R and poisson regression and have a few questions. I have count data of incidents per month, a couple years prior to an intervention and 1 year after. I want to use poisson ...
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Variable selection in Bayesian spatio-temporal count regression

I am estimating a Bayesian spatio-temporal Poisson model. I have a relatively large set of explanatory variables (20ish) and each time I run the model it takes a few hours to complete. I have seen ...
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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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Statistical analysis for quasi-experiments

This is my first message on this forum. I hope I am not doing any mistake. I must analyze data obtained after a quasi-experiment and I am not sure how to proceed. The experiment has been carried out ...
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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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Are over-dispersion tests in GLMs actually *useful*?

The phenomenon of 'over-dispersion' in a GLM arises whenever we use a model that restricts the variance of the response variable, and the data exhibits greater variance than the model restriction ...
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Spatio-tempral Bayesian Poisson model convergence investigation

I am fitting a spatio-temporal Bayesian Poisson model with 22 explanatory variables, an offset variable, 2200 observations and non-informative priors. I am using the package ...
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Which regression used for normalized count data

I am working with social network data. I have multiple networks of various sizes and I'm calculating indegree (the number of connections between people) in each of the networks. I've been told to ...
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How to isolate the effect of dichotomous predictor?

I want to isolate gender differences in preferences for a particular attribute of a product based on data available about their product purchases. I understand that I have to use a mixed Poisson ...
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Fitting a (maybe Poisson) regression to my data in R

I'm trying to understand the probability distribution for my data. Each point represents an individual patient, the 0 or 1 label indicates whether they have a particular disease, and the number of ...
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Regression discontinuity - optimal bandwidth choice

I have a very basic question. I would like to implement a nonparametric RD but I have a Poisson outcome variable. I would like to select the proper bandwidth and my question is about which method to ...
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Are Poisson Regressions with Serial Correlation Biased or Inconsistent? (No Fixed Effects)

Let's say I've got panel data where a count outcome $y$ and continuous independent variable $x$ observed each time period $t=(1,2,...T)$ for each individual $i$. I am interested in how $x_{it}$ ...
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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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Logistic regression vs Poisson log link

The exercise is to predict the success rate for different groups of students. Here's sample data (using R): ...
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R: Chi-squared comparing one reference group to two other groups

If this question has been answered elsewhere, please direct me to the appropriate post. thank you! Below is an example of part of my data. I am trying to determine if there is a statistically ...
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Underlying Poisson Distribution in Cox Regression with censoring

My question stems from this post: Does Cox Regression have an underlying Poisson distribution? Cox regression with no censoring can be interpreted as Poisson regression. Can we interpret Cox ...
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Combining centrality into one based on same data type

I'm working on a project that involves count data (specifically number of interactions) from multiple different districts in a specific area. Our team has been talking about calculating a few ...
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Experimental design for simulation experiment

I'm interested in investigating the effect of a treatment on survival times of a patient. The "patient" is a complex program with many interacting categorical and continuous variables. It also has a ...
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How to perform over-dispersion test where null is quasi-Poisson

If I understand correctly, a quasi Poisson regression assumes roughly that $$ \mbox{E}\left[y\left|x\right.\right] = \exp{\left(x^{\top}\beta\right)}, \quad \mbox{VAR}\left(y\left|x\right.\right) = \...
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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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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 ...