TY  - JOUR
T1  - Bayesian Spatial Change of Support for Count-Valued Survey Data with Application to the American Community Survey
JF  - Journal of the American Statistical Association
Y1  - 2015
A1  - Bradley, Jonathan
A1  - Wikle, C.K.
A1  - Holan, S. H.
AB  - We introduce Bayesian spatial change of support methodology for count-valued survey data with known survey variances. Our proposed methodology is motivated by the American Community Survey (ACS), an ongoing survey administered by the U.S. Census Bureau that provides timely information on several key demographic variables. Specifically, the ACS produces 1-year, 3-year, and 5-year “period-estimates,” and corresponding margins of errors, for published demographic and socio-economic variables recorded over predefined geographies within the United States. Despite the availability of these predefined geographies it is often of interest to data-users to specify customized user-defined spatial supports. In particular, it is useful to estimate demographic variables defined on “new” spatial supports in “real-time.” This problem is known as spatial change of support (COS), which is typically performed under the assumption that the data follows a Gaussian distribution. However, count-valued survey data is naturally non-Gaussian and, hence, we consider modeling these data using a Poisson distribution. Additionally, survey-data are often accompanied by estimates of error, which we incorporate into our analysis. We interpret Poisson count-valued data in small areas as an aggregation of events from a spatial point process. This approach provides us with the flexibility necessary to allow ACS users to consider a variety of spatial supports in “real-time.” We show the effectiveness of our approach through a simulated example as well as through an analysis using public-use ACS data.
UR  - http://www.tandfonline.com/doi/abs/10.1080/01621459.2015.1117471
ER  - 

TY  - RPRT
T1  - NCRN Meeting Spring 2015: Regionalization of Multiscale Spatial Processes Using a Criterion for Spatial Aggregation Error
Y1  - 2015
A1  - Wikle, Christopher K.
A1  - Bradley, Jonathan
A1  - Holan, Scott
AB  - NCRN Meeting Spring 2015: Regionalization of Multiscale Spatial Processes Using a Criterion for Spatial Aggregation Error Wikle, Christopher K.; Bradley, Jonathan; Holan, Scott Develop and implement a statistical criterion to diagnose spatial aggregation error that can facilitate the choice of regionalizations of spatial data. Presentation at NCRN Meeting Spring 2015
PB  - NCRN Coordinating Office
UR  - http://hdl.handle.net/1813/40177
ER  - 

TY  - RPRT
T1  - NCRN Meeting Fall 2014: Mixed Effects Modeling for Multivariate-Spatio-Temporal Areal Data
Y1  - 2014
A1  - Bradley, Jonathan
A1  - Holan, Scott
A1  - Wikle, Christopher
AB  - NCRN Meeting Fall 2014: Mixed Effects Modeling for Multivariate-Spatio-Temporal Areal Data Bradley, Jonathan; Holan, Scott; Wikle, Christopher Presentation from NCRN Fall 2014 meeting
PB  - NCRN Coordinating Office
UR  - http://hdl.handle.net/1813/37749
ER  -