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Modelling Key Population Attrition in the HIV and AIDS Programme in Kenya Using Random Survival Forests with Synthetic Minority Oversampling Technique-Nominal Continuous

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Journal of Data Analysis and Information Processing 2023年第1期11卷 11-36页

作者： Evan Kahacho charity wamwea Bonface Malenje Gordon Aomo Department of Statistics and Actuarial Sciences Jomo Kenyatta University of Agriculture and Technology Nairobi Kenya Monitoring and Evaluation Kenya Red Cross Society-Global Fund Unit Nairobi Kenya

HIV and AIDS has continued to be a major public health concern, and hence one of the epidemics that the world resolved to end by 2030 as highlighted in sustainable development goals (SDGs). A colossal amount of effort has been taken to reduce new HIV infections, but there are still a significant number of new infections reported. HIV prevalence is more skewed towards the key population who include female sex workers (FSW), men who have sex with men (MSM), and people who inject drugs (PWID). The study design was retrospective and focused on key population enrolled in a comprehensive HIV and AIDS programme by the Kenya Red Cross Society from July 2019 to June 2021. Individuals who were either lost to follow up, defaulted (dropped out, transferred out, or relocated) or died were classified as attrition;while those who were active and alive by the end of the study were classified as retention. The study used density analysis to determine the spatial differences of key population attrition in the 19 targeted counties, and used Kilifi county as an example to map attrition cases in smaller administrative areas (sub-county level). The study used synthetic minority oversampling technique-nominal continuous (SMOTE-NC) to balance the datasets since the cases of attrition were much less than retention. The random survival forests model was then fitted to the balanced dataset. The model correctly identified attrition cases using the predicted ensemble mortality and their survival time using the estimated Kaplan-Meier survival function. The predictive performance of the model was strong and way better than random chance with concordance indices greater than 0.75.

关键词： Random Survival Forests Synthetic Minority Oversampling Technique-Nominal Continuous (SMOTE-NC) Key Population Female Sex Workers (FSW) Men Who Have Sex with Men (MSM) People Who Inject Drugs (PWID)

Consistency of the <i>φ</i>-Divergence Based Change Point Estimator

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Open Journal of Statistics 2020年第5期10卷 832-849页

作者： Mwelu Susan Anthony G. Waititu Peter N. Mwita charity wamwea Pan-African University Institute of Basic Sciences Technology and Innovation Nairobi Kenya Department of Statistics and Actuarial Sciences JKUAT Nairobi Kenya Department of Mathematics Statistics and Actuarial Sciences Machakos University Machakos Kenya

This paper utilizes a change-point estimator based on the φ-divergence. Since we seek a near perfect translation to reality, then locations of parameter change within a finite set of data have to be accounted for since the assumption of stationary model is too restrictive especially for long time series. The estimator is shown to be consistent through asymptotic theory and finally proven through simulations. The estimator is applied to the generalized Pareto distribution to estimate changes in the scale and shape parameters.

关键词： Change Point Consistency φ-Divergence Kullback-Leibler Generalized Pareto Distribution

Limit Distribution of the φ-Divergence Based Change Point Estimator

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Open Journal of Statistics 2021年第3期11卷 337-350页

作者： Mwelu Susan Anthony G. Waititu Peter N. Mwita charity wamwea Pan African University Institute for Basic Sciences Technology and Innovation Nairobi Kenya Department of Statistics and Actuarial Sciences JKUAT Nairobi Kenya Department of Mathematics Statistics and Actuarial Sciences Machakos University Machakos Kenya

The assumption of stationarity is too restrictive especially for long time series. This paper studies the change point problem through a change point estimator based on the φ-divergence which provides a rich set of distance like measures between pairs of distributions. The change point problem is considered in the following sub-fields: the problem of divergence estimation, testing for the homogeneity between two samples as well as estimating the time of change. The asymptotic distribution of the change point estimator is estimated by the limiting distribution of a stochastic process within given bounds through asymptotic theory surrounding the likelihood theory. The distribution is found to converge to that of a standardized Brownian bridge process.

关键词： Change Point φ-Divergence Estimator Test Statistic Distribution Wald

Consistency of the φ -Divergence Based Change Point Estimator

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