Literature DB >> 10875185

Standardization and decomposition of rates: useful analytic techniques for behavior and health studies.

J Wang1, A Rahman, H A Siegal, J H Fisher.   

Abstract

Standardization and decomposition are widely used analytic techniques in population studies for adjusting the impact of compositional factors on rates. This study demonstrates the application of these methods to behavior and health studies. Bootstrapping is used to estimate standard errors of the component effects and to conduct significance tests for them. The authors have developed a Windows-based computer program that is demonstrated in the study for standardization and decomposition analysis by using empirical data on HIV seropositivity rates in two injection-drug-using populations in the northeastern United States.

Mesh:

Year:  2000        PMID: 10875185     DOI: 10.3758/bf03207806

Source DB:  PubMed          Journal:  Behav Res Methods Instrum Comput        ISSN: 0743-3808


  10 in total

1.  Regional differences in HIV prevalence and individual attitudes among service providers in China.

Authors:  Li Li; Chunqing Lin; Zunyou Wu; W Scott Comulada; Yingying Ding
Journal:  Soc Sci Med       Date:  2012-04-12       Impact factor: 4.634

2.  Revisiting Das Gupta: refinement and extension of standardization and decomposition.

Authors:  Albert Chevan; Michael Sutherland
Journal:  Demography       Date:  2009-08

3.  Explaining regional disparities in traffic mortality by decomposing conditional probabilities.

Authors:  Gregory P Goldstein; David E Clark; Lori L Travis; Amy E Haskins
Journal:  Inj Prev       Date:  2011-01-06       Impact factor: 2.399

4.  Main drivers of health expenditure growth in China: a decomposition analysis.

Authors:  Tiemin Zhai; John Goss; Jinjing Li
Journal:  BMC Health Serv Res       Date:  2017-03-09       Impact factor: 2.655

5.  The role of residential mobility in reproducing socioeconomic stratification during the transition to adulthood.

Authors:  Anne Clark
Journal:  Demogr Res       Date:  2018-01-12

6.  A new method to attribute differences in total deaths between groups to population size, age structure and age-specific mortality rate.

Authors:  Xunjie Cheng; Liheng Tan; Yuyan Gao; Yang Yang; David C Schwebel; Guoqing Hu
Journal:  PLoS One       Date:  2019-05-10       Impact factor: 3.240

7.  Understanding Differences in Cancer Survival between Populations: A New Approach and Application to Breast Cancer Survival Differentials between Danish Regions.

Authors:  Marie-Pier Bergeron-Boucher; Jim Oeppen; Niels Vilstrup Holm; Hanne Melgaard Nielsen; Rune Lindahl-Jacobsen; Maarten Jan Wensink
Journal:  Int J Environ Res Public Health       Date:  2019-08-26       Impact factor: 3.390

8.  Quantifying the excess risk of infant mortality based on race/ethnicity at the county level to inform Michigan's home visiting outreach plans.

Authors:  Patricia McKane; Sarah Lyon-Callo; Nancy Peeler; Paulette Dobynes Dunbar; Brenda Fink
Journal:  PLoS One       Date:  2018-09-12       Impact factor: 3.240

9.  Standardization of medical service indicators: A useful technique for hospital administration.

Authors:  Li Wu; Conghua Ji; Hanti Lu; Xuewen Hong; Shan Liu; Ying Zhang; Qiushuang Li; Sijia Huang; Penglei Zhou; Jiong Yao; Yuxiu Hu
Journal:  PLoS One       Date:  2018-11-28       Impact factor: 3.240

10.  Estimation of the relationship between the persistent decrease of the suicide rate and the changes in sociodemographic composition in Hungary between 1990 and 2011.

Authors:  Lajos Balint; Katalin Fuzer; Xenia Gonda; Peter Dome
Journal:  PLoS One       Date:  2020-10-23       Impact factor: 3.240

  10 in total

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