Search Results - "Mwalili, Samuel"

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  1. 1

    SEIR model for COVID-19 dynamics incorporating the environment and social distancing by Mwalili, Samuel, Kimathi, Mark, Ojiambo, Viona, Gathungu, Duncan, Mbogo, Rachel

    Published in BMC research notes (23-07-2020)
    “…Coronavirus disease 2019 (COVID-19) is a pandemic respiratory illness spreading from person-to-person caused by a novel coronavirus and poses a serious public…”
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    Journal Article
  2. 2

    Effect of climate on incidence of respiratory syncytial virus infections in a refugee camp in Kenya: A non-Gaussian time-series analysis by Nyoka, Raymond, Omony, Jimmy, Mwalili, Samuel M, Achia, Thomas N O, Gichangi, Anthony, Mwambi, Henry

    Published in PloS one (01-06-2017)
    “…Respiratory syncytial virus (RSV) is one of the major causes of acute lower respiratory tract infections (ALRTI) in children. Children younger than 1 year are…”
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    Journal Article
  3. 3

    Modified sharp regression discontinuity model to settings with fuzzy variables by Mafukidze, Portia K, Mwalili, Samuel M, Mageto, Thomas

    Published in BMC research notes (18-10-2023)
    “…The goal of this study is to develop a Modified Sharp Regression Discontinuity model to predict alcohol consumption in People Living with Human…”
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    Journal Article
  4. 4

    svy_logistic_regression: A generic SAS macro for simple and multiple logistic regression and creating quality publication-ready tables using survey or non-survey data by Muthusi, Jacques, Mwalili, Samuel, Young, Peter

    Published in PloS one (03-09-2019)
    “…Reproducible research is increasingly gaining interest in the research community. Automating the production of research manuscript tables from statistical…”
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    Journal Article
  5. 5

    Flexible Bayesian semiparametric mixed-effects model for skewed longitudinal data by Ferede, Melkamu M, Dagne, Getachew A, Mwalili, Samuel M, Bilchut, Workagegnehu H, Engida, Habtamu A, Karanja, Simon M

    Published in BMC medical research methodology (01-03-2024)
    “…In clinical trials and epidemiological research, mixed-effects models are commonly used to examine population-level and subject-specific trajectories of…”
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  6. 6

    Age-structured model for COVID-19: Effectiveness of social distancing and contact reduction in Kenya by Kimathi, Mark, Mwalili, Samuel, Ojiambo, Viona, Gathungu, Duncan Kioi

    Published in Infectious disease modelling (01-01-2021)
    “…Coronavirus disease 2019 is caused by severe acute respiratory syndrome coronavirus 2. Kenya reported its first case on March 13, 2020 and by March 16, 2020…”
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  7. 7

    Forecasting the spread of the COVID-19 pandemic in Kenya using SEIR and ARIMA models by Kiarie, Joyce, Mwalili, Samuel, Mbogo, Rachel

    Published in Infectious disease modelling (01-06-2022)
    “…COVID-19, a coronavirus disease 2019, is an ongoing pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The first case in Kenya…”
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  8. 8

    New Test for the Comparison of Survival Curves to Detect Late Differences by Nizeyimana, Ildephonse, Mwalili, Samuel, Orwa, George

    Published in Journal of probability and statistics (01-03-2023)
    “…Background. Survival analysis attracted the attention of different scientists from various domains such as engineering, health, and social sciences. It has…”
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  9. 9

    Flexible Parametric Accelerated Hazard Model: Simulation and Application to Censored Lifetime Data with Crossing Survival Curves by Muse, Abdisalam Hassan, Chesneau, Christophe, Ngesa, Oscar, Mwalili, Samuel

    “…This study aims to propose a flexible, fully parametric hazard-based regression model for censored time-to-event data with crossing survival curves. We call it…”
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  10. 10

    The zero-inflated negative binomial regression model with correction for misclassification: an example in caries research by Mwalili, Samuel M, Lesaffre, Emmanuel, Declerck, Dominique

    Published in Statistical methods in medical research (01-04-2008)
    “…Zero-inflated models for count data are becoming quite popular nowadays and are found in many application areas, such as medicine, economics, biology,…”
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  11. 11

    Understanding the Evolving Role of Voluntary Medical Male Circumcision as a Public Health Strategy in Eastern and Southern Africa: Opportunities and Challenges by Bershteyn, Anna, Mudimu, Edinah, Platais, Ingrida, Mwalili, Samuel, Zulu, James E., Mwanza, Wiza N., Kripke, Katharine

    Published in Current HIV/AIDS reports (01-12-2022)
    “…Purpose of Review Voluntary male medical circumcision (VMMC) has been a cornerstone of HIV prevention in Eastern and Southern Africa (ESA) and is credited in…”
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    Journal Article
  12. 12

    Does Air Pollution Trigger Infant Mortality in Western Europe? A Case-Crossover Study by Scheers, Hans, Mwalili, Samuel M., Faes, Christel, Fierens, Frans, Nemery, Benoit, Nawrot, Tim S.

    Published in Environmental health perspectives (01-07-2011)
    “…Background: Numerous studies show associations between tine particulate air pollutants [paniculate matter with an aerodynamic diameter < 10 μm (PM₁₀)] and…”
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  13. 13

    Bayesian and frequentist approach for the generalized log-logistic accelerated failure time model with applications to larynx-cancer patients by Muse, Abdisalam Hassan, Mwalili, Samuel, Ngesa, Oscar, Alshanbari, Huda M., Khosa, Saima Khan, Hussam, Eslam

    Published in Alexandria engineering journal (01-10-2022)
    “…The log-normal, log-logistic and Weibull distributions are commonly utilized to model survival data. Unimodal (or non-monotone) failure rate functions are…”
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  14. 14

    Modelling trends of CD4 counts for patients on antiretroviral therapy (ART): a comprehensive health care clinic in Nairobi, Kenya by Mugo, Caroline W, Shkedy, Ziv, Mwalili, Samuel, Awoke, Tadesse, Braekers, Roel, Wandede, Dolphine, Mwachari, Christina

    Published in BMC infectious diseases (04-01-2022)
    “…In resource-limited settings, changes in CD4 counts constitute an important component in patient monitoring and evaluation of treatment response as these…”
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  15. 15

    Employing phylogenetic tree shape statistics to resolve the underlying host population structure by Kayondo, Hassan W, Ssekagiri, Alfred, Nabakooza, Grace, Bbosa, Nicholas, Ssemwanga, Deogratius, Kaleebu, Pontiano, Mwalili, Samuel, Mango, John M, Leigh Brown, Andrew J, Saenz, Roberto A, Galiwango, Ronald, Kitayimbwa, John M

    Published in BMC bioinformatics (10-11-2021)
    “…Host population structure is a key determinant of pathogen and infectious disease transmission patterns. Pathogen phylogenetic trees are useful tools to reveal…”
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  17. 17

    A General Method for Dealing with Misclassification in Regression: The Misclassification SIMEX by Küchenhoff, Helmut, Mwalili, Samuel M., Lesaffre, Emmanuel

    Published in Biometrics (01-03-2006)
    “…We have developed a new general approach for handling misclassification in discrete covariates or responses in regression models. The simulation and…”
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  18. 18

    Bayesian rank likelihood-based estimation: An application to low birth weight in Ethiopia by Bekalo, Daniel Biftu, Wanjoya, Anthony Kibira, Mwalili, Samuel Musili

    Published in PloS one (31-05-2024)
    “…Low birth weight is a significant risk factor associated with high rates of neonatal and infant mortality, particularly in developing countries. However, most…”
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  19. 19

    Bayesian and Frequentist Approaches for a Tractable Parametric General Class of Hazard-Based Regression Models: An Application to Oncology Data by Muse, Abdisalam Hassan, Mwalili, Samuel, Ngesa, Oscar, Chesneau, Christophe, Al-Bossly, Afrah, El-Morshedy, Mahmoud

    Published in Mathematics (Basel) (01-10-2022)
    “…In this study, we consider a general, flexible, parametric hazard-based regression model for censored lifetime data with covariates and term it the “general…”
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    Journal Article
  20. 20

    svy_freqs: A Generic SAS Macro for Creating Publication-Quality Three-Way Cross-Tabulations by Muthusi, Jacques, Young, Peter W, Mwalili, Samuel

    Published in Journal of open research software (2021)
    “…Cross-tabulations are a simple but important tool for understanding the distribution of socio-demographic characteristics among participants in epidemiological…”
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