Model-based imputation of missing data from the 122 Cities Mortality Reporting System (122 CMRS)
Moraga, Paula & Ozonoff, Al (2015) Model-based imputation of missing data from the 122 Cities Mortality Reporting System (122 CMRS). Stochastic Environmental Research and Risk Assessment, 29(5), pp. 1499-1507.
National estimates of the all-cause and pneumonia and influenza (P&I) mortality burden derived from U.S. influenza surveillance data treat all missing or unreported values as zero counts. The effect of this methodological decision is to undercount influenza deaths, thus biasing estimates downward and producing underestimates of the true mortality burden. In this paper, a regression-based procedure is proposed to impute missing values and thus produce a more accurate estimate of mortality. Several model specifications are considered and evaluated to predict weekly death counts by city, calendar week, calendar year and age group. Revised all-cause, P&I and excess mortality estimates are calculated by imputing the missing data. The impact of the treatment of unreported mortality data on national estimates is evaluated by comparing the estimates obtained using data with and without imputation. This comparison reflects some differences in mortality burden, excess deaths, and trends over time. The model presented is a useful approach to impute missing counts and improve inference in situations with modest occurrence of missing data.
Impact and interest:
Citation counts are sourced monthly from and citation databases.
These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.
Citations counts from theindexing service can be viewed at the linked Google Scholar™ search.
|Item Type:||Journal Article|
|Keywords:||Influenza surveillance, Excess mortality, Missing data, Serfling method|
|Divisions:||Current > Research Centres > ARC Centre of Excellence for Mathematical & Statistical Frontiers (ACEMS)
Current > Schools > School of Mathematical Sciences
Current > QUT Faculties and Divisions > Science & Engineering Faculty
|Copyright Owner:||Copyright 2014 Springer-Verlag Berlin Heidelberg|
|Deposited On:||22 May 2016 22:27|
|Last Modified:||23 May 2016 21:23|
Repository Staff Only: item control page