JSM 2013 Home
Online Program Home
My Program

Abstract Details

Activity Number: 142
Type: Contributed
Date/Time: Monday, August 5, 2013 : 8:30 AM to 10:20 AM
Sponsor: Government Statistics Section
Abstract - #310252
Title: Model-Based Targeted Address Canvassing: A Simulation Based on the 2009 Address Canvassing Program
Author(s): John Boies*+ and Kevin M. Shaw and Jonathan Holland
Companies: U.S. Census Bureau and U.S. Census Bureau and U.S. Census Bureau
Keywords: Decennial Census ; Cost/Benefit Analysis ; Address Canvassing ; Simulation ; Modeling ; Logistic Regression
Abstract:

We use data from the 2009 Census Addressing Canvassing (AC) operationto conduct a "What If" simulation of a model based "targeted" AC program where census blocks are selected for canvassing based on their predicted probabilities of deviating from the master address file's data. Covariates measuring block characteristics of two kinds-physical structure, e.g., housing unit count, characteristics, and social structure, e.g., demographics-were used to predict 11 different canvassing outcomes. The results indicate that both physical and social structure are important predictors of whether blocks warrant a visit by field representatives. Some interesting results include that the number of housing units in a block is negatively related to residential change once other variables, e.g., multi-unit structure composition and social structure variables, e.g., age, sex composition are introduced into the models. The research indicates that models to predict which blocks should be targeted for canvassing can be developed and that this approach could result in substantial savings of time and money in preparation for the 2020 Decennial Census with a minimal affect on Census quality.


Authors who are presenting talks have a * after their name.

Back to the full JSM 2013 program




2013 JSM Online Program Home

For information, contact jsm@amstat.org or phone (888) 231-3473.

If you have questions about the Continuing Education program, please contact the Education Department.

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

ASA Meetings Department  •  732 North Washington Street, Alexandria, VA 22314  •  (703) 684-1221  •  meetings@amstat.org
Copyright © American Statistical Association.