Home > Publications . Search All . Browse All . Country . Browse PSC Pubs . PSC Report Series

PSC In The News

RSS Feed icon

Levy says ACA has helped increase rates of insured, but rates still lowest among poor

Bruch reveals key decision criteria in making first cuts on dating sites

Murphy on extending health support via a smart phone and JITAI

More News

Highlights

U-M ranked #4 in USN&WR's top public universities

Frey's new report explores how the changing US electorate could shape the next 5 presidential elections, 2016 to 2032

U-M's Data Science Initiative offers expanded consulting services via CSCAR

Elizabeth Bruch promoted to Associate Professor

Next Brown Bag

Mon, Sept 19 at noon:
Paradox of Unintended Pregnancy, Jennifer Barber

Loglinear residual tests of Moran's I autocorrelation and their applications to Kentucky breast cancer data

Publication Abstract

Lin, Ge, and T.L. Zhang. 2007. "Loglinear residual tests of Moran's I autocorrelation and their applications to Kentucky breast cancer data." Geographical Analysis, 39:293-310.

This article bridges the permutation test of Moran's I to the residuals of a loglinear model under the asymptotic normality assumption. It provides the versions of Moran's I based on Pearson residuals (I-PR) and deviance residuals (I-DR) so that they can be used to test for spatial clustering while at the same time account for potential covariates and heterogeneous population sizes. Our simulations showed that both I-PR and I-DR are effective to account for heterogeneous population sizes. The tests based on I-PR and I-DR are applied to a set of log-rate models for early-stage and late-stage breast cancer with socioeconomic and access-to-care data in Kentucky. The results showed that socioeconomic and access-to-care variables can sufficiently explain spatial clustering of early-stage breast carcinomas, but these factors cannot explain that for the late stage. For this reason, we used local spatial association terms and located four late-stage breast cancer clusters that could not be explained. The results also confirmed our expectation that a high screening level would be associated with a high incidence rate of early-stage disease, which in turn would reduce late-stage incidence rates.

DOI:10.1111/j.1538-4632.2007.00705.x (Full Text)

Browse | Search : All Pubs | Next