Why is Poisson regression used for count data? - Cross Validated
64 Poisson distributed data is intrinsically integer-valued, which makes sense for count data. Ordinary Least Squares (OLS, which you call "linear regression") assumes that true values are …
log transforming a Poisson variable - Cross Validated
Jul 23, 2022 · Trying to understand how log-transforming a count variable changes the regression equation. The reason I ask is because I see a lot of researchers log-transform their data so …
When to use an offset in a Poisson regression? [duplicate]
Does anybody know why offset in a Poisson regression is used? What do you achieve by this?
Poisson regression to estimate relative risk for binary outcomes
From Poisson regression, relative risks can be reported, which some have argued are easier to interpret compared with odds ratios, especially for frequent outcomes, and especially by …
In a Poisson model, what is the difference between using time as a ...
Oct 4, 2015 · the Poisson distribution, named after French mathematician Siméon Denis Poisson, is a discrete probability distribution that expresses the probability of a given number of events …
How to interpret coefficients in a Poisson regression?
This was in discussions of interpreting logistic regression coefficients, but Poisson regression is similar if you use an offset of time at risk to get rates. You add first all the coefficients …
regression - What is the appropriate model for underdispersed …
The best --- and standard ways to handle underdispersed Poisson data is by using a generalized Poisson, or perhaps a hurdle model. Three parameter count models can also be used for …
Poisson regression for binary data - Cross Validated
I've been trying to read up on Poisson regression models, and it looks like it is possible to estimate such a model with a binary outcome. This has come up before on this site here (and …
Log-likelihood function in Poisson Regression - Cross Validated
In Poisson regression, I need to compute the deviance, in order to do that I need to compute the log-likelihood function. It seems not difficult because I have the estimated model and my data …
How to check for multicollinearity in Poisson regression model …
Apr 24, 2023 · I have created a Poisson regression model with robust error variance (https://academic.oup.com/aje/article/159/7/702/71883) to calculate relative risks. This is the …