#POISSON REGRESSION STATA SOFTWARE#

The assumption here is that, for example, every day in rehab makes a patient equally likely to have an aggressive incident. What this means theoretically is that by defining an offset variable, you are only adjusting for the amount of opportunity an event has. The coefficient of 1 allows you to theoretically move it back to the left side of the equation to turn your count back into a rate. One important feature of an offset variable is that it is required to have a coefficient of 1. Only Stata allows you to define either the exposure or the offset variable.

#POISSON REGRESSION STATA SOFTWARE#

Most statistical software will require you to create the logged variable and define it as the offset variable. This logged variable, ln(exposure), is called the offset variable. When both sides of the equation are then logged, the final model contains ln(exposure) as a term that is added to the regression coefficients. If the rate is count/exposure, multiplying both sides of the equation by exposure moves it to the right side of the equation. Poisson models handle exposure variables by using simple algebra to change the dependent variable from a rate into a count.

A count of 10 incidents out of 180 days is much smaller than a count of 10 out of 15. But if there is variation in the number of days each patient is present, attendance itself could affect the count. If all patients are in the center the same number of days, a rate is unnecessary. The first example would not need a rate, but the second probably will. Using these regression models gives much more accurate parameter estimates than trying to fit an ordinary linear regression model whose assumptions rarely fit count data such as normal residuals and constant variance.Д«ut how do the Poisson models handle rates? A rate is just a count per unit time. Poisson regression models allow researchers to examine the relationship between predictors and count outcome variables. Most count variables follow one of these distributions in the Poisson family. вЂ“ Number of aggressive incidents performed by patients in an impatient rehab center

вЂ“ Number of words an eighteen month old can say A few examples of count variables include: Poisson Regression Models and its extensions (Zero-Inflated Poisson, Negative Binomial Regression, etc.) are used to model counts and rates.

Poisson regression stata