Simulation and sensitivity analysis of the choice of open interval, the methods of open interval, the methods of estimating life expectancy, completeness and 6 in the SEG method of estimating mortality

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dc.contributor.advisorDorrington, Roben_ZA
dc.contributor.authorMsemburi, Willliamen_ZA
dc.date.accessioned2014-07-31T12:39:40Z
dc.date.available2014-07-31T12:39:40Z
dc.date.issued2010en_ZA
dc.description.abstractDeath distribution methods, particularly the Generalized Growth Balance (GGB) and the Synthetic Extinct Generations (SEG) methods, have been observed to lead to the most accurate estimates when estimating mortality [1]. The more general version of the SEG method corrects for differential coverage of censuses directly by adding a constant (6) to the age-specific growth rates such that the correction leads to a horizontal series of age specific estimates of completeness. This research attempts to obtain the best variation of this version of the SEG method from a range of choices for an open interval age as well as well as methods of estimating life expectancy. completeness and 6. This task is accomplished by starting with a base population with known mortality then applying random errors in completeness. age misstatement and net migration to it to generate numerous datasets consisting of simulated census counts and simulated vital registration deaths by age. Variations of the SEG method are then applied to the simulated datasets to correct for the underestimation of mortality caused by the data errors. The best variations are found by statistical analysis of the difference between the true mortality and the estimated mortality for each variation and dataset generated. Using the Coale and Demeny model life tables to estimate life expectancy. selecting the a that results in a minimum variance in the age specific estimates of completeness. estimating completeness using the median value of the age specific. estimates Of completeness for ages 15 and older and using the 85+ age group for the open interval is observed to be the variation of the SEG method that leads to the most accurate estimates of mortality.en_ZA
dc.identifier.apacitationMsemburi, W. (2010). <i>Simulation and sensitivity analysis of the choice of open interval, the methods of open interval, the methods of estimating life expectancy, completeness and 6 in the SEG method of estimating mortality</i>. (Thesis). University of Cape Town ,Faculty of Commerce ,Centre for Actuarial Research (CARE). Retrieved from http://hdl.handle.net/11427/5893en_ZA
dc.identifier.chicagocitationMsemburi, Willliam. <i>"Simulation and sensitivity analysis of the choice of open interval, the methods of open interval, the methods of estimating life expectancy, completeness and 6 in the SEG method of estimating mortality."</i> Thesis., University of Cape Town ,Faculty of Commerce ,Centre for Actuarial Research (CARE), 2010. http://hdl.handle.net/11427/5893en_ZA
dc.identifier.citationMsemburi, W. 2010. Simulation and sensitivity analysis of the choice of open interval, the methods of open interval, the methods of estimating life expectancy, completeness and 6 in the SEG method of estimating mortality. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Msemburi, Willliam AB - Death distribution methods, particularly the Generalized Growth Balance (GGB) and the Synthetic Extinct Generations (SEG) methods, have been observed to lead to the most accurate estimates when estimating mortality [1]. The more general version of the SEG method corrects for differential coverage of censuses directly by adding a constant (6) to the age-specific growth rates such that the correction leads to a horizontal series of age specific estimates of completeness. This research attempts to obtain the best variation of this version of the SEG method from a range of choices for an open interval age as well as well as methods of estimating life expectancy. completeness and 6. This task is accomplished by starting with a base population with known mortality then applying random errors in completeness. age misstatement and net migration to it to generate numerous datasets consisting of simulated census counts and simulated vital registration deaths by age. Variations of the SEG method are then applied to the simulated datasets to correct for the underestimation of mortality caused by the data errors. The best variations are found by statistical analysis of the difference between the true mortality and the estimated mortality for each variation and dataset generated. Using the Coale and Demeny model life tables to estimate life expectancy. selecting the a that results in a minimum variance in the age specific estimates of completeness. estimating completeness using the median value of the age specific. estimates Of completeness for ages 15 and older and using the 85+ age group for the open interval is observed to be the variation of the SEG method that leads to the most accurate estimates of mortality. DA - 2010 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2010 T1 - Simulation and sensitivity analysis of the choice of open interval, the methods of open interval, the methods of estimating life expectancy, completeness and 6 in the SEG method of estimating mortality TI - Simulation and sensitivity analysis of the choice of open interval, the methods of open interval, the methods of estimating life expectancy, completeness and 6 in the SEG method of estimating mortality UR - http://hdl.handle.net/11427/5893 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/5893
dc.identifier.vancouvercitationMsemburi W. Simulation and sensitivity analysis of the choice of open interval, the methods of open interval, the methods of estimating life expectancy, completeness and 6 in the SEG method of estimating mortality. [Thesis]. University of Cape Town ,Faculty of Commerce ,Centre for Actuarial Research (CARE), 2010 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/5893en_ZA
dc.language.isoeng
dc.publisher.departmentCentre for Actuarial Research (CARE)en_ZA
dc.publisher.facultyFaculty of Commerceen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.subject.otherDemographyen_ZA
dc.titleSimulation and sensitivity analysis of the choice of open interval, the methods of open interval, the methods of estimating life expectancy, completeness and 6 in the SEG method of estimating mortalityen_ZA
dc.typeMaster Thesis
dc.type.qualificationlevelMasters
dc.type.qualificationnameMComen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceThesisen_ZA
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