American Journal of Theoretical and Applied Statistics

Volume 7, Issue 1, January 2018

  • Application of Cox Regression in Modeling Survival Rate of Drug Abuse

    Robert Kasisi, Joseph Koske, Mathew Kosgei

    Issue: Volume 7, Issue 1, January 2018
    Pages: 1-7
    Received: Jun. 28, 2017
    Accepted: Jul. 10, 2017
    Published: Dec. 20, 2017
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    Abstract: Drug and substance abuse is a serious health problem in many countries. In Kenya drug abuse is one of the leading causes of mortality. Modeling the rate of survival of drug users involves determining time to relapse of drug users and the number of treatment episodes for full recovery. A study of the treatment programs that the subjects are enrolled... Show More
  • Modeling Primary School Absenteeism and Academic Performance in Ethiopia: A Multivariate and Count Regression Models Approaches

    Edossa Merga Terefe, Zeytu Gashaw Asfaw

    Issue: Volume 7, Issue 1, January 2018
    Pages: 8-20
    Received: Nov. 21, 2017
    Accepted: Dec. 01, 2017
    Published: Jan. 05, 2018
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    Abstract: School absenteeism and low academic performance at primary schools remain a big issue for developing countries like Ethiopia. Thus, this study aims to determine predicting factors influencing academic performances and school absenteeism jointly at primary schools in Ethiopia. A cross-sectional data were obtained from the Young Lives project from wa... Show More
  • Gaussian Longitudinal Analysis of Progression of Diabetes Mellitus Patients Using Fasting Blood Sugar Level: A Case of Debre Berhan Referral Hospital, Ethiopia

    Wudneh Ketema Moges, A. R. Muralidharan, Haymanot Zeleke Tadesse

    Issue: Volume 7, Issue 1, January 2018
    Pages: 21-28
    Received: Nov. 21, 2017
    Accepted: Dec. 04, 2017
    Published: Jan. 09, 2018
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    Abstract: Diabetes mellitus is a metabolic disorder where by glucose cannot effectively get transported out of the blood. It is a chronic disease with a high prevalence and growing concern in world wide. There are two Types of diabetes, which are Type I and Type II. A longitudinal data analysis retrospective based study was conducted between 1st September, 2... Show More
  • A More Robust Random Effects Model for Disease Mapping

    Tonui Benard Cheruiyot, Mwalili Samuel, Wanjoya Anthony

    Issue: Volume 7, Issue 1, January 2018
    Pages: 29-34
    Received: Dec. 20, 2017
    Accepted: Jan. 08, 2018
    Published: Jan. 19, 2018
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    Abstract: Disease mapping studies have found wide applications within geographical epidemiology and public health and are typically analysed within a Bayesian hierarchical model formulation. The most popular disease mapping model is the Besag-York-Molli´e model. A distinguishing feature of this model is the use of two sets of random effects: one spatially st... Show More
  • Desirability and Design of Experiments Applied to the Optimization of the Reduction of Decarburization of the Process Heat Treatment for Steel Wire Sae 51B35

    Cristie Diego Pimenta, Messias Borges Silva, Rose Lima de Morais Campos, Walfredo Ribeiro de Campos Junior

    Issue: Volume 7, Issue 1, January 2018
    Pages: 35-44
    Received: Dec. 26, 2017
    Accepted: Jan. 10, 2018
    Published: Jan. 23, 2018
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    Abstract: This study contributes directly to the understanding of the causative agent of loss of carbon steel wire during the heat treatment (phenomenon called decarburization). This carbon loss disqualifies the material for your applications originally envisaged, as with mechanical reduction of the amount of the chemical element carbon steel becomes less re... Show More