Extended version of zero-inflated negative binomial distribution with application to HIV exposed infant count data

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dc.contributor.authorDr.Odhiambo, Collins
dc.contributor.authorKibika, Stella
dc.date.accessioned2020-08-19T09:14:52Z
dc.date.available2020-08-19T09:14:52Z
dc.date.issued2019-09-17
dc.descriptionResearch Brown Bag Presentationsen_US
dc.description.abstractRoutine HIV exposed infants (HEI) data that is collected monthly depicts many HIV positive zeros due to prevention of mother-to-child transmission (PMTCT) policy. However, since implementation of PMTCT differs both geographically and facility-by-facility, there is likelihood of structured zero for HEI positive numbers (optimum PMTCT) and non-structured zero (sub-optimum PMTCT). Hence standard zero-inflated models may not be appropriate. This project seeks to extend the zero-inflated Negative Binomial (ZINB) model by incorporating Shanker distribution. Extensive simulations were conducted by varying parameters in the model, i.e. dispersion, shape and sample size. Results were compared using BC. The model was tested using HEI data sampled from six high HIV burden counties in Kenya. Both simulation and real HEI data results show that the model yielded better performance.en_US
dc.description.sponsorshipStrathmore Institute of Mathematical Sciencesen_US
dc.identifier.urihttp://hdl.handle.net/11071/9513
dc.language.isoen_USen_US
dc.publisherStrathmore Universityen_US
dc.relation.ispartofseriesReserch Brown Bag;BB2019.E35
dc.subjectHIVen_US
dc.subjectDiseasesen_US
dc.subjectHIV preventionen_US
dc.titleExtended version of zero-inflated negative binomial distribution with application to HIV exposed infant count dataen_US
dc.typePresentationen_US
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