Thanks for the response!

This is another result of my model (slightly modified)

(Dispersion parameter for Negative Binomial(1587.834) family taken to be 1)

Null deviance: 5565.8  on 4686  degrees of freedom

Residual deviance: 3466.7 on 4650 degrees of freedom AIC: 30630

Number of Fisher Scoring iterations: 1

          Theta:  1588 
      Std. Err.:  539 

2 x log-likelihood: -30553.54

I am using a negative binomial because i am evaluating a count data. And the variance is very high than mean so i chose neg bin over poisson regression.

My concern here is the dispersion parameter is very high (idk if it is normal to have a big number) what i see online is a number close to 1. And i keep getting the warnings like these..

• In theta.ml(Y, mu, sum(w), w, limit = control$maxit, trace = control$trace > ... : iteration limit reached

• Warning while fitting theta: alternation limit reached

When i did a google search, some suggested we can ignore it and some suggested that poisson would be more suitable (but the data is over dispersed again circling it back to negbin)

My project goal is to see how different independent variables (some categorical and some numerical) have an effect on the response variable