Re: st: which -cmp- option to use for poisson model with count data?

[David Hoaglin <dchoaglin@gmail.com>]

We may need to give more attention to a sentence in the message that
Laura sent about 12 hours ago: "Consulting another expert can also
depend on what the last one had said."  If such a process is at work,
the data involve a different form of dependence.  It might be
described as clustering of events within individual.  Perhaps Poisson,
with the rate changing within individual.  If what the previous expert
said is in the available data, a model should try to use that
information.

David Hoaglin

On Mon, May 7, 2012 at 11:07 PM, Cameron McIntosh <cnm100@hotmail.com> wrote:
> Laura,
> Yes, the "independence of observations" assumption that Nick mentions below could be violated due to a complex survey design with stratification and clustering (or clustering of cases due to any number of possible reasons).  This can be dealt with:
> Lu, M., & Yang, W. (2012). Multivariate Logistic Regression Analysis of Complex Survey Data with Application to BRFSS Data. Journal of Data Science 10, 157-173.
>
> Moore, C.G., Lipsitz, S.R., Addy, C.L., Hussey, J.R., Fitzmaurice, G., & Natarajan, S. (2009). Logistic regression with incomplete covariate data in complex survey sampling: application of reweighted estimating equations. Epidemiology, 20(3), 382-390.
>
> If you want to use an ordered regression model with count data, you can consider the counts as thresholds on a latent response variate (i.e., propensity to consult experts in this case):
>
> Kasteridis, P.P., Munkin, M.K. ,& Yen, S.T. (2010). Demand for cigarettes: a mixed binary-ordered probit approach. Applied Economics, 42(4), 413-426.

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