> From:
[hidden email]> Subject: Re: different result in two nb reg and pisson reg
> To:
[hidden email]>
> The increases in the standard errors are larger than I might guess, but
> off-hand they don't suggest anything inherently strange going on in the
> estimated models.
>
> A few notes:
>
> - You have warnings about convergence for both models in the Model Effects
> table.
> - The intercept for all of the models shown is really large. The variable
> "time.travel" is coded in time format, so I suspect SPSS is predicting time
> travel in seconds. May be best to physically change these to integers
> representing minutes. (This might also help SPSS converge to a solution in
> the model effects tables)
> - In the negative binomial model you restrict the dispersion parameter to
> be equal to 1. Most situations I would imagine you want to estimate it from
> the data, e.g. "DISTRIBUTION=NEGBIN(MLE)"
>
> More generally:
>
> I can't tell from this data whether you should be fitting a Poisson model
> at all! It is quite possible a better fitting model is to simply take the
> log of minutes - if time.travel needs to be transformed at all. You have a
> restricted range of time.travel from 5 minutes to 4.5 hours, suggesting that
> a Poisson or Neg Bin model may substantially deviate from the observations
> -- especially in the tails. [Both will assign mass to the [0 to <= 5] minute
> range, but with a large mean estimate the mass will be very small.]
>
> Try looking at a histogram of travel time and see you can draw a reasonable
> fit line for Poisson or a Negative Binomial Model over top of it. [Given no
> times are below 5 minutes I'm tempted to suggest looking at censored models,
> but it is speculation given the limited info. you've provided.]
>
> The variance in the DESCRIPTIVES is somewhat misleading for the same time
> format reason I previously stated. You also have no point mass at 0, so
> there is nothing wrong off hand in taking the logs (if the log of time
> travel theoretically makes sense.)
>
> More could said about the models estimated (e.g. it appears you use SPLIT
> FILE, but you may consider stacking the models and estimating them +
> interactions all at once). [Also it isn't clear the nature of the categories
> of time and how they relate to one another.] But hopefully this is enough to
> chew on for a bit ;)
>
>