What causes overdispersion Poisson?
Overdispersion occurs due to such factors as the presence greater variance of response variable caused by other variables unobserved heterogeneity, the influence of other variables which leads to dependence of the probability of an event on previous events, the presence of outliers, the existence of excess zeros on …
What does Equidispersion mean?
In statistics, overdispersion is the presence of greater variability (statistical dispersion) in a data set than would be expected based on a given statistical model. Conversely, underdispersion means that there was less variation in the data than predicted.
What does large standard error of intercept-Statalist mean?
When we run a regression (e.g. ordinary least squares, or probit) with an intercept, if our estimate of the intercept has a very large standard error, does it say anything bad about the model? Does it have something to do with the skewness of the data?
Which is the intercept of a parametric model?
So, the intercept is E (y|x1 = 0, x2 = 0., xk = 0) and this often is an impossible parameter to estimate well (even with a parametric model). Moreover, it is often not all al interesting, as x1 = 0., xk = 0 is not an interesting population.
Why are there high standard errors in ml SE?
If in doubt and your data are all categorical, it can be appropriate and informative to check your results against an exact test or chi square. As for “high standard errors”, model ML SE is the reliability of parameter estimates based upon the data, not a measure of the reliability of your data per se.
Why is there a huge standard error for a simple regression?
I was initially running a multinomial logistic regression, with multiple predictors. However, the standard error turned out to be huge for the parameters. So, I ran a simple logistic regression with just one predictor, but the standard error was still huge.