RE: st: Time Series Poisson

[Richard Williams <richardwilliams.ndu@gmail.com>]

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: tirthankar.chakravarty@gmail.com
> > To: statalist@hsphsun2.harvard.edu
> >
> > Richard,
> >
> > See chapter 4 in this book:
> > http://amzn.com/0471363553
> >
> > T
> >
> >
> > On Sun, Oct 30, 2011 at 6:53 PM, Richard Williams
> > <richardwilliams.ndu@gmail.com> 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:  Richard.A.Williams.5@ND.Edu
> > > WWW:    http://www.nd.edu/~rwilliam
> > >
> > > *
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> > > *   http://www.ats.ucla.edu/stat/stata/
> > >
> >
> >
> >
> > --
> > Tirthankar Chakravarty
> > tchakravarty@ucsd.edu
> > tirthankar.chakravarty@gmail.com
> >
> > *
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> > *   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:  Richard.A.Williams.5@ND.Edu
WWW:    http://www.nd.edu/~rwilliam


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