Modeling Counts of Census Responses over a Span of Time

For a survey or census, it may be of interest to understand the nature in which responses arrive over time during the operation. Tendencies may vary with subsets of the population - such as those sharing geographic regions or non-geographic characteristics - in ways that can be interesting or informative in planning subsequent operations. This work considers the application of panel count models to daily counts of responses from the 2020 Decennial Census. These data are publicly available at several levels of geography. Panel count models are more commonly used in biostatistics to study counts of recurrent events which occur within a subject between observation times. The framework will be applied to the present setting, with special considerations to account for some of the interesting features of the data.

Bayesian

Poisson

Regression

Finite Mixture

Gibbs Sampler 

Data Science Applications

Symposium on Data Science and Statistics (SDSS) 2026