Eric J. Feuer
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Research Subjects
Eric J. Feuer has a total of 154 co-authors. Here are the top co-authors by number of shared publications:
- Benmei Liu
National Cancer Institute 1 Surveillance Research Program, Division of Cancer Control and Population Sciences Bethesda, Maryland
34 shared publications - Recinda L. Sherman
North American Association of Central Cancer Registries Springfield Illinois USA
17 shared publications - James Cucinelli
Information Management Services, Inc., Calverton, Maryland
16 shared publications - Jeremy Lyman
Information Management Services, Inc., Calverton, Maryland
16 shared publications - Li Zhu
Surveillance Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, U.S.A.
16 shared publications - Zaria Tatalovich
National Cancer Institute 1 Surveillance Research Program, Division of Cancer Control and Population Sciences Bethesda, Maryland
16 shared publications
Latest Publications
- Open Access
- 2 June 2026
- Published by American Association for Cancer Research (AACR)
Figure S3 from Spatiotemporal Modeling Approach to Mapping Geographic and Temporal Variation in Cancer Incidence Rates for US Counties
Supplementary Figure S3 shows comparison of yearly counts: modeled vs observed counts for five relatively less common cancers.
- 2 June 2026
- Published by American Association for Cancer Research (AACR)
Open AccessFigure S3 from Spatiotemporal Modeling Approach to Mapping Geographic and Temporal Variation in Cancer Incidence Rates for US Counties
Supplementary Figure S3 shows comparison of yearly counts: modeled vs observed counts for five relatively less common cancers.
- Open Access
- 2 June 2026
- Published by American Association for Cancer Research (AACR)
Table S2 from Spatiotemporal Modeling Approach to Mapping Geographic and Temporal Variation in Cancer Incidence Rates for US Counties
Supplementary Table S2 lists the pool of covariates from years 2005 to 2019 and data sources.
- 2 June 2026
- Published by American Association for Cancer Research (AACR)
Open AccessTable S2 from Spatiotemporal Modeling Approach to Mapping Geographic and Temporal Variation in Cancer Incidence Rates for US Counties
Supplementary Table S2 lists the pool of covariates from years 2005 to 2019 and data sources.
- Open Access
- 2 June 2026
- Published by American Association for Cancer Research (AACR)
Figure S1 from Spatiotemporal Modeling Approach to Mapping Geographic and Temporal Variation in Cancer Incidence Rates for US Counties
Supplementary Figure S1 shows comparison of the yearly counts: modeled vs observed counts for all cancer sites combined (female).
- 2 June 2026
- Published by American Association for Cancer Research (AACR)
Open AccessFigure S1 from Spatiotemporal Modeling Approach to Mapping Geographic and Temporal Variation in Cancer Incidence Rates for US Counties
Supplementary Figure S1 shows comparison of the yearly counts: modeled vs observed counts for all cancer sites combined (female).
- Open Access
- 2 June 2026
- Published by American Association for Cancer Research (AACR)
Figure S6 from Spatiotemporal Modeling Approach to Mapping Geographic and Temporal Variation in Cancer Incidence Rates for US Counties
Supplementary Figure S6 shows ratios of county-level observed to modeled age-adjusted incidence rates for five selected cancer sites.
- 2 June 2026
- Published by American Association for Cancer Research (AACR)
Open AccessFigure S6 from Spatiotemporal Modeling Approach to Mapping Geographic and Temporal Variation in Cancer Incidence Rates for US Counties
Supplementary Figure S6 shows ratios of county-level observed to modeled age-adjusted incidence rates for five selected cancer sites.
- Open Access
- 2 June 2026
- Published by American Association for Cancer Research (AACR)
Table S1 from Spatiotemporal Modeling Approach to Mapping Geographic and Temporal Variation in Cancer Incidence Rates for US Counties
Supplementary Table S1 includes the pool of cancer sites where the 16 sex-specific cancer sites were selected from.
- 2 June 2026
- Published by American Association for Cancer Research (AACR)
Open AccessTable S1 from Spatiotemporal Modeling Approach to Mapping Geographic and Temporal Variation in Cancer Incidence Rates for US Counties
Supplementary Table S1 includes the pool of cancer sites where the 16 sex-specific cancer sites were selected from.
- Open Access
- 2 June 2026
- Published by American Association for Cancer Research (AACR)
Figure S5 from Spatiotemporal Modeling Approach to Mapping Geographic and Temporal Variation in Cancer Incidence Rates for US Counties
Supplementary Figure S5 shows ratios of county-level observed to modeled age-adjusted incidence rates for five selected cancer sites.
- 2 June 2026
- Published by American Association for Cancer Research (AACR)
Open AccessFigure S5 from Spatiotemporal Modeling Approach to Mapping Geographic and Temporal Variation in Cancer Incidence Rates for US Counties
Supplementary Figure S5 shows ratios of county-level observed to modeled age-adjusted incidence rates for five selected cancer sites.
- Open Access
- 2 June 2026
- Published by American Association for Cancer Research (AACR)
Figure S4 from Spatiotemporal Modeling Approach to Mapping Geographic and Temporal Variation in Cancer Incidence Rates for US Counties
Supplementary Figure S4 shows comparison of yearly counts: modeled vs observed counts for four rare cancers.
- 2 June 2026
- Published by American Association for Cancer Research (AACR)
Open AccessFigure S4 from Spatiotemporal Modeling Approach to Mapping Geographic and Temporal Variation in Cancer Incidence Rates for US Counties
Supplementary Figure S4 shows comparison of yearly counts: modeled vs observed counts for four rare cancers.
- Open Access
- 2 June 2026
- Published by American Association for Cancer Research (AACR)
Table S3 from Spatiotemporal Modeling Approach to Mapping Geographic and Temporal Variation in Cancer Incidence Rates for US Counties
Supplementary Table S3 shows results from the exploratory model comparison for prior selection: DIC & WAIC from the standard Poisson model (Model 1) with different spatial random effect assumptions (Besag2 and Leroux) for the 16 selected cancer sites.
- 2 June 2026
- Published by American Association for Cancer Research (AACR)
Open AccessTable S3 from Spatiotemporal Modeling Approach to Mapping Geographic and Temporal Variation in Cancer Incidence Rates for US Counties
Supplementary Table S3 shows results from the exploratory model comparison for prior selection: DIC & WAIC from the standard Poisson model (Model 1) with different spatial random effect assumptions (Besag2 and Leroux) for the 16 selected cancer sites.
- Open Access
- 2 June 2026
- Published by American Association for Cancer Research (AACR)
Model Descriptions from Spatiotemporal Modeling Approach to Mapping Geographic and Temporal Variation in Cancer Incidence Rates for US Counties
Supplementary Model Descriptions provides additional details on the models assumed for the random effects and hyperparameters.
- 2 June 2026
- Published by American Association for Cancer Research (AACR)
Open AccessModel Descriptions from Spatiotemporal Modeling Approach to Mapping Geographic and Temporal Variation in Cancer Incidence Rates for US Counties
Supplementary Model Descriptions provides additional details on the models assumed for the random effects and hyperparameters.
- Open Access
- 2 June 2026
- Published by American Association for Cancer Research (AACR)
Figure S2 from Spatiotemporal Modeling Approach to Mapping Geographic and Temporal Variation in Cancer Incidence Rates for US Counties
Supplemental Figure S2 shows comparison of yearly counts: modeled vs observed counts for multiple common cancers.
- 2 June 2026
- Published by American Association for Cancer Research (AACR)
Open AccessFigure S2 from Spatiotemporal Modeling Approach to Mapping Geographic and Temporal Variation in Cancer Incidence Rates for US Counties
Supplemental Figure S2 shows comparison of yearly counts: modeled vs observed counts for multiple common cancers.