A hierarchical Bayesian approach for the analysis of longitudinal count data with overdispersion: A simulation study
AbstractIn sets of count data, the sample variance is often considerably larger or smaller than the sample mean, known as a problem of over- or underdispersion. The focus is on hierarchical Bayesian modeling of such longitudinal count data. Two different models are considered. The first one assumes a Poisson distribution for the count data and includes a subject-specific intercept, which is assumed to follow a normal distribution, to account for subject heterogeneity. However, such a model does not fully address the potential problem of extra-Poisson dispersion. The second model, therefore, includes also random subject and time dependent parameters, assumed to be gamma distributed for reasons of conjugacy. To compare the performance of the two models, a simulation study is conducted in which the mean squared error, relative bias, and variance of the posterior means are compared.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Elsevier in its journal Computational Statistics & Data Analysis.
Volume (Year): 57 (2013)
Issue (Month): 1 ()
Contact details of provider:
Web page: http://www.elsevier.com/locate/csda
Deviance information criteria; Hierarchical Poisson–Normal model (HPN); Hierarchical Poisson–Normal overdispersed model (HPNOD); Overdispersion;
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Hinde, John & Demetrio, Clarice G. B., 1998. "Overdispersion: Models and estimation," Computational Statistics & Data Analysis, Elsevier, vol. 27(2), pages 151-170, April.
- Iddi, Samuel & Molenberghs, Geert, 2012. "A combined overdispersed and marginalized multilevel model," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1944-1951.
- Pryseley, Assam & Tchonlafi, Clotaire & Verbeke, Geert & Molenberghs, Geert, 2011. "Estimating negative variance components from Gaussian and non-Gaussian data: A mixed models approach," Computational Statistics & Data Analysis, Elsevier, vol. 55(2), pages 1071-1085, February.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.