ENBIS-17 in Naples

9 – 14 September 2017; Naples (Italy) Abstract submission: 21 November 2016 – 10 May 2017

My abstracts

 

The following abstracts have been accepted for this event:

  • On Jackknife-After-Bootstrap Method for Dependent Data

    Authors: Ufuk Beyaztas (Istanbul Medeniyet University), Beste H. Beyaztas (Istanbul Medeniyet University)
    Primary area of focus / application: Modelling
    Secondary area of focus / application: Finance
    Keywords: Financial Time Series, Prediction, Resampling methods, Simulation
    Submitted at 6-May-2017 19:42 by Ufuk Beyaztas
    Accepted (view paper)
    13-Sep-2017 09:00 On Jackknife-After-Bootstrap Method for Dependent Data
    In this study, we adapt sufficient and ordered non-overlapping block bootstrap techniques into the Jackknife-after-Bootstrap (JaB) algorithm to evaluate the precision of the bootstrap estimators under dependent data. To this end, we obtain JaB estimates of the statistics under consideration and obtain their quantities such as coverage probability to compare the performances of different JaB methods. We also extend the JaB algorithm to obtain prediction intervals for future returns and volatilities of GARCH processes. The finite sample properties of the proposed methods are illustrated by an extensive simulation study and they are applied to S&P500 stock index data. Our findings reveal that the proposed algorithm often exhibits improved performance and, is computationally more efficient compared to conventional JaB method.
  • On Bootstrapping in Individual Bioequivalence

    Authors: Beste Hamiye Beyaztas (İstanbul Medeniyet University), Ufuk Beyaztas (Istanbul Medeniyet University)
    Primary area of focus / application: Design and analysis of experiments
    Keywords: Bioequivalence, Bootstrap, Design of Experiment, Hypothesis testing
    Submitted at 6-May-2017 20:45 by Beste Hamiye Beyaztas
    Accepted (view paper)
    12-Sep-2017 14:30 On Bootstrapping in Individual Bioequivalence
    Bioequivalence (BE) studies play an important role in the drug development process. The goal of such studies is to evaluate the therapeutic equivalence of two (or more) drugs or to study if two different galenic formulations of the same drug have a similar bioavailability and therapeutic effect. The bioequivalence methods developed in the literature are basically divided into three groups as average, population and individual bioequivalence (IBE). When testing statistical hypothesis of IBE, the method of confidence interval is usually used. Since the parameter used in the hypothesis is in a non-linear form, it is difficult to determine the exact distributions of this parameter analytically and therefore to calculate the confidence interval to be used for testing hypothesis. To overcome this problem, the United States Food and Drug Administration has recommended the use of a non-parametric bootstrap method.

    In this study, we propose to use sufficient bootstrap method, which uses only distinct units in a bootstrap sample, to assess the individual bioequivalence under 2 × 4 randomized crossover design. The finite sample properties of the proposed algorithm are illustrated by an extensive simulation study and a real world example. Our results reveal that the proposed test procedure have a more power with less variability and computation time compared to the conventional methods.
  • Material Handling Equipment Selection Using UTASTAR

    Authors: Zeynep Dur (Hacettepe University), Guldal Guleryuz (Hacettepe University)
    Primary area of focus / application: Business
    Secondary area of focus / application: Modelling
    Keywords: Material handling, Equipment selection, UTASTAR, Multi criteria decision making
    Submitted at 7-May-2017 19:23 by Guldal Guleryuz
    Accepted
    12-Sep-2017 14:30 Material Handling Equipment Selection Using UTASTAR
    Choosing the appropriate material handling equipment positively affects the efficiency of handling the materials in production facilities. Delays in production, high lead times, defects and high production costs might be associated with unsuitable material handling systems. If the needs and requirements of the facility are not properly identified, material handling system will not conform to facility operations. For movement type operations, type and characteristics of the material as well as the type and characteristics of the movement plays important role. Equipment is a major part in Material handling system. If designing the whole material handling system is the main problem, then choosing the right equipment is one of the biggest sub problems. Many of the approaches to equipment selection problem focuses on multi criteria decision making methods, knowledge based systems or analytic methods or the combination of these approaches. This study applies a utility additive type (UTASTAR) method to crane selection problem for a steel fabrication factory. Potential alternatives and the criteria are determined using decision makers’ opinions and preferences are obtained. Ranking of the alternatives are found and the results are compared to analytical approach solution.
  • Operating Room Targeted Time Analysis and Scheduling: A Case Study for a Large Teaching Hospital

    Authors: Seda Albayrak (Hacettepe University), Guldal Guleryuz (Hacettepe University)
    Primary area of focus / application: Modelling
    Secondary area of focus / application: Business
    Keywords: OR scheduling, Block allocation, OR utilization, Targeted time
    Submitted at 7-May-2017 19:29 by Guldal Guleryuz
    Accepted
    11-Sep-2017 16:40 Operating Room Targeted Time Analysis and Scheduling: A Case Study for a Large Teaching Hospital
    Costs resulting from surgeries have a big share in a hospital’s budget. Efficient operating room scheduling can help hospitals lower the costs by minimizing under-utilization and over-utilization. Block scheduling, which allocates a particular amount of time on given days of the week to surgical groups is widely used in hospitals. Block scheduling either allows for flexibility such as by changing the block allocations on a weekly/monthly basis, or can be very restrictive by dictating the same schedule for every week/month. In this paper, a large teaching hospital with 25 operating rooms is considered. The hospital uses very restricted block scheduling with a constant operating room schedule throughout the year. Target time for the surgical groups is analyzed to identify if current time allocation is suitable for the needs and goals of the hospital and surgical groups. Due to incomplete data, analysis is provided only on the basis of recent operations. Utilizations of the operating rooms on a daily basis are obtained; over-utilized and under-utilized blocks are identified. How to assign specific operating rooms to surgical groups on specific days of the week is examined.
  • Keeping Indecision of Respondents in Composite Indicators

    Authors: Stefania Capecchi (University of Naples Federico II), Rosaria Simone (University of Naples Federico II), Domenico Piccolo (University of Naples Federico II)
    Primary area of focus / application: Modelling
    Keywords: Composite indicators, Uncertainty, CUB models, Ordinal data
    Submitted at 8-May-2017 10:11 by Domenico Piccolo
    Accepted (view paper)
    12-Sep-2017 14:50 Keeping Indecision of Respondents in Composite Indicators
    Composite indicators are valuable tools to quantify the overall assessment of a latent trait provided by multi-item surveys. This feature is important in dealing with massive data set. Several proposals have arisen in the literature in order to meet different objectives and to measure various aspects of the data.
    In case evaluations are collected by means of ordinal scales, a mixture model has been developed to take the data generating process into account. In this approach, the final rating is interpreted as the combination of an agreement towards the item under investigation and an inherent indecision accompanying the decision-making process. Such an uncertainty measure accounts for the overall nuisances affecting a fully meditated response. This parametric approach has turned out to be a very effective tool to perform an item by item analysis of questionnaires and comparisons among different items can be effectively yet simply based on similarity among the corresponding agreement and uncertainty parameters.
    In order to project CUB models methodology in a multi-item framework, the present contribution aims at integrating it in the process of selection of composite indicators. This task is pursued by exploiting a simple graphical representation of CUB models: thus, composite indicators are mapped in the parameter space after suitable ordinal transformation and CUB estimation. As compared with standard approaches, a distinctive feature of the proposal consists in retaining the level of uncertainty which is generally present in questionnaire analysis.
    A case study analyzed via the R package supports the effectiveness of the proposal.
  • The Problems with Construction and Interpretation of Shewhart Control Charts

    Authors: Vladimir Shper (Moscow Institute of Steel & Alloys), Yuri Adler (Moscow Institute of Steel & Alloys)
    Primary area of focus / application: Process
    Secondary area of focus / application: Education & Thinking
    Keywords: SPC, Shewhart, Control, Chart, Application
    Submitted at 8-May-2017 12:06 by Vladimir Shper
    Accepted (view paper)
    11-Sep-2017 16:40 The Problems with Construction and Interpretation of Shewhart Control Charts
    In this paper we discuss the problems of using Shewhart Control Charts (SCC) in numerous applications. We enlist and classify the main problems one encounters in practice, explain our view on the causes of these problem emergence and suppose the ways to avoid or mitigate the confusion due to misusing of SCC. There are both well-known (e.g., the collection and use of baseline data in Phase I) and little-known (e.g., the importance of point order) issues within the scope of our analysis. And we try to establish the link between different issues because we are sure that many of them are caused by a general systemic reason: misunderstanding the difference between the so-called analytic and enumerative studies. Though our attention is focused firstly on the help to practitioners some problems within statistical community are analyzed as well. Examples from real processes and some results of simulations are also presented. Our main goal is to decrease the gap between the theory and practice in the area of statistical process control (SPC).