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A Fit of Kaplan Meire Maternal Mortality In Narok County Maasai Mara University School of Science Department of Mathematics and Physical Sciences

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dc.contributor.author Mutinda, Kimeu Martin
dc.date.accessioned 2016-03-05T12:56:24Z
dc.date.available 2016-03-05T12:56:24Z
dc.date.issued 2014-04
dc.identifier.uri http://hdl.handle.net/123456789/1948
dc.description.abstract This research was both quantitative and qualitative.it was a ca e study based in Narok county hospital because it has the capacity both in human resource aspect and facility. The study took into account the serial period tatting May 20 13-Feb 2014. Under this study the Kaplan meire was used to estimate the probability of survival using Survival curve .The hazard function was used to estimate the instantaneous death rate or the failure time. The Kaplan-Meier nonparametric method to estimate the empirical hazard survivor and cumulative distribution functions. The hazard function was of the interest in this study as it will estimate the probability of the event happening (death) occurring. The cox regression model been used to look into factors that influences maternal mortality My case study will be based in Narok district and specifically Narok district Hospital. Data was from the Narok District Hospital health recorded 34.04% of the patients were not married (Single) while the married were 64.9% of the total population ds recorded in clinic cards . For instance, the probability a woman will survive beyond 4 weeks after giving birth is 92.9% while for a patient to survive beyond the 6th week is has a survival probability at 89.3% .The mean of the two period were then be compared using standard normal- statistic(95% confidence interval).Other categorical have been compared using chi-square distribution. Statistical package for Social Sciences (SPSS ) software was used find all the estimates under Kaplan rneire and the cox regression. en_US
dc.language.iso en en_US
dc.title A Fit of Kaplan Meire Maternal Mortality In Narok County Maasai Mara University School of Science Department of Mathematics and Physical Sciences en_US
dc.type Article en_US


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