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RE: st: Time Series Poisson


From   Richard Williams <[email protected]>
To   [email protected]
Subject   RE: st: Time Series Poisson
Date   Sun, 30 Oct 2011 23:46:55 -0500

Thanks Cameron and Tirthankar. Many of these look promising. To be clear, there is only 1 country involved here, with separate records for each of 45 years. Some of these sources sound like they might be designed for cross-sectional time series rather than time series, but I don't understand either well enough to really say. (And I am still hoping for that nifty Stata-specific solution, since I am not sure how far we will get if we have to figure out how to program this ourselves!)

At 08:42 PM 10/30/2011, Cameron McIntosh wrote:
Hi Richard, Tirthankar
I might also suggest:
Oh, M.-S., & Lim, Y.B. (2001). Bayesian analysis of time series Poisson data. Journal of Applied Statistics, 28(2), 259-271. Drescher, D. (2008). Testing for presence of a latent process in count series. Journal of Statistical Computation and Simulation, 78(7), 595-607. Jung, R.C., Kukuk, M., & Liesenfeld, R. (2006). Time series of count data: modeling, estimation and diagnostics. Computational Statistics & Data Analysis, 51(4), 2350-2364. Jorgensen, B., Lundbye-Christensen, S., Song, P.X-K., & Sun, Li. (1999). A State Space Model for Multivariate Longitudinal Count Data. Biometrika, 86(1), 169-181. Knape, J., Jonzén, N., Sköld, M., & Sokolov, L. (2009). Multivariate state-space modelling of bird migration count data. Environmental and Ecological Statistics, 3(Section I), 59-79. Knape et al. (2009) model a 54-year time series of various bird species counts, your student might follow their Bayesian strategy... I was also thinking that it might be possible to fit a latent growth curve or multilevel model to this type of data, with Poisson links on the 45 indicators: Liu, H. (2007). Growth Curve Models for Zero-Inflated Count Data: An Application to Smoking Behavior. Structural Equation Modeling, 14(2), 247-279. Alosh, M. (2009). Modeling longitudinal count data with dropouts. Pharmaceutical Statistics, 9(1), 35-45. Min, Y., & Agresti, A. (2005). Random effect models for repeated measures of zero-inflated count data. Statistical Modelling, 5(1), 1-19. Coelho-Barrosa, E.A., Achcar, J.A., & Mazucheli, J. (2010). Longitudinal Poisson modeling: an application for CD4 counting in HIV-infected patients. Journal of Applied Statistics, 37(5), 865-880.
My two cents,
Cam
> Date: Sun, 30 Oct 2011 18:04:46 -0700
> Subject: Re: st: Time Series Poisson
> From: [email protected]
> To: [email protected]
>
> Richard,
>
> See chapter 4 in this book:
> http://amzn.com/0471363553
>
> T
>
>
> On Sun, Oct 30, 2011 at 6:53 PM, Richard Williams
> <[email protected]> wrote:
> > One of my students (a political scientist of course -- they always bring up > > these weird problems I have never encountered myself!) has a data set that > > consists of 45 yearly records for the United States. The dependent variable > > is a count. It sounded to me like the sort of thing that should be analyzed > > by a time series poisson model. But, unfortunately, I wasn't even sure that
> > such a thing existed - I was hoping there was a tspoisson command, but no
> > such luck.
> >
> > However, I found this Stata Technical Bulletin for a very old user-written > > command called nwest. http://www.stata.com/products/stb/journals/stb39.pdf. > > It says "This article discusses the calculation of standard errors that are > > robust to heteroscedasticity and serial correlation for probit, logit, and
> > poisson regression models."
> >
> > I also found this slightly newer post from 2003:
> > http://www.stata.com/statalist/archive/2003-06/msg00258.html.
> >
> > What I take from this is that he should -tsset- his data and use -glm- to
> > estimate a Poisson model with Newey-West standard errors, e.g. something
> > like
> >
> > glm y x1 x2 x3, family(poisson) link(log) vce(hac nwest)
> >
> > Does this sound right, and if so is this the best he can do, at least with
> > Stata?
> >
> >
> > -------------------------------------------
> > Richard Williams, Notre Dame Dept of Sociology
> > OFFICE: (574)631-6668, (574)631-6463
> > HOME:   (574)289-5227
> > EMAIL:  [email protected]
> > WWW:    http://www.nd.edu/~rwilliam
> >
> > *
> > *   For searches and help try:
> > *   http://www.stata.com/help.cgi?search
> > *   http://www.stata.com/support/statalist/faq
> > *   http://www.ats.ucla.edu/stat/stata/
> >
>
>
>
> --
> Tirthankar Chakravarty
> [email protected]
> [email protected]
>
> *
> *   For searches and help try:
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> *   http://www.stata.com/support/statalist/faq
> *   http://www.ats.ucla.edu/stat/stata/

*
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-------------------------------------------
Richard Williams, Notre Dame Dept of Sociology
OFFICE: (574)631-6668, (574)631-6463
HOME:   (574)289-5227
EMAIL:  [email protected]
WWW:    http://www.nd.edu/~rwilliam


*
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*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/


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