Literature DB >> 12155410

Mixed model for analyzing geographic variability in mortality rates.

R K Tsutakawa.   

Abstract

"A mixed model is proposed for the analysis of geographic variability in mortality rates. In addition to demographic parameters and random geographic parameters, the model includes additional random-effects parameters to adjust for extra-Poisson variability. The model uses a gamma-Poisson distribution with a random scale parameter having an inverse gamma prior. An empirical Bayes approach is used to estimate relative risks for geographic regions and annual rates for demographic groups within each region. Lung cancer in Missouri is used to motivate and illustrate the procedure." excerpt

Entities:  

Keywords:  Americas; Cancer; Causes Of Death; Demographic Factors; Developed Countries; Developing Countries; Differential Mortality; Diseases; Geographic Factors; Methodological Studies; Missouri; Models, Theoretical; Mortality; Neoplasms; North America; Northern America; Population; Population Dynamics; Pulmonary Effects; Research Methodology; United States

Mesh:

Year:  1988        PMID: 12155410     DOI: 10.1080/01621459.1988.10478562

Source DB:  PubMed          Journal:  J Am Stat Assoc        ISSN: 0162-1459            Impact factor:   5.033


  9 in total

1.  Maternal mortality estimation at the subnational level: a model-based method with an application to Bangladesh.

Authors:  Saifuddin Ahmed; Kenneth Hill
Journal:  Bull World Health Organ       Date:  2010-06-29       Impact factor: 9.408

2.  What is too much variation? The null hypothesis in small-area analysis.

Authors:  P Diehr; K Cain; F Connell; E Volinn
Journal:  Health Serv Res       Date:  1990-02       Impact factor: 3.402

3.  A hierarchical finite mixture model that accommodates zero-inflated counts, non-independence, and heterogeneity.

Authors:  Charity J Morgan; Mark F Lenzenweger; Donald B Rubin; Deborah L Levy
Journal:  Stat Med       Date:  2014-01-20       Impact factor: 2.373

4.  Testing the null hypothesis in small area analysis.

Authors:  K C Cain; P Diehr
Journal:  Health Serv Res       Date:  1992-08       Impact factor: 3.402

5.  Assessment of spatial variation of risks in small populations.

Authors:  W B Riggan; K G Manton; J P Creason; M A Woodbury; E Stallard
Journal:  Environ Health Perspect       Date:  1991-12       Impact factor: 9.031

6.  Applying and comparing empirical and full Bayesian models in study of evaluating relative risk of suicide among counties of Ilam province.

Authors:  Behzad Mahaki; Yadollah Mehrabi; Amir Kavousi; Youkhabeh Mohammadian; Mehdi Kargar
Journal:  J Educ Health Promot       Date:  2015-08-06

7.  Geographic patterns of poor HIV/AIDS care continuum in District of Columbia.

Authors:  Suparna Das; Jenevieve Opoku; Michael Kharfen; Adam Allston
Journal:  AIDS Res Ther       Date:  2018-01-24       Impact factor: 2.250

8.  Bayesian hierarchical models for disease mapping applied to contagious pathologies.

Authors:  Sylvain Coly; Myriam Garrido; David Abrial; Anne-Françoise Yao
Journal:  PLoS One       Date:  2021-01-13       Impact factor: 3.240

9.  Bayesian disease mapping: Past, present, and future.

Authors:  Ying C MacNab
Journal:  Spat Stat       Date:  2022-01-19
  9 in total

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