Multi-Road User Simulation: Methodological Considerations from Study Planning to Data Analysis

2017 ◽  
pp. 403-418 ◽  
Author(s):  
Dominik Muehlbacher ◽  
Katharina Preuk ◽  
Christian Lehsing ◽  
Sebastian Will ◽  
Mandy Dotzauer
2019 ◽  
Vol 2 (1) ◽  
pp. 11
Author(s):  
Nurul Hidayati ◽  
Agung Erwanda

This study focused on the behavior of road user (biker/rider), especially around the Gendengan Intersection in Surakarta. This study aims to determine the types of violations, the causes, and effects that occur around the intersection. The primary data used are observation data of violations and questionnaires of 400 respondents. This study also uses data of traffic accidents and violations from the SATLANTAS of Surakarta Police and the IRSMS of KORLANTAS POLRI. The analysis refers to Law No.22 of 2009. Based on the Police data analysis, there are 87.98% of violations in Surakarta related to driver behavior, while using the primary data it was found around 48.32%. Lack of awareness of orderly traffic causes the driver to ignore his safety. This can be seen from the percentage of respondents who answered YES greater than NO happening in almost all violation types. Traffic violations can be a major factor in traffic accidents. Therefore, the implementation of strict rules needs to be done for those who violate, either in the form of fines or imprisonment. Penelitian ini difokuskan pada perilaku berlalu lintas pengendara di jalan, khususnya di sekitar Simpang Gendengan Surakarta. Penelitian ini bertujuan untuk mengetahui tipe-tipe pelanggaran, penyebab dan dampak pelanggaran yang terjadi di sekitar simpang tersebut. Data primer yang digunakan adalah data pengamatan lapangan dan kuesioner dari 400 responden. Penelitian ini juga menggunakan data kecelakaan dan pelanggaran lalu lintas dari Satlantas Polresta Surakarta dan IRSMS KORLANTAS POLRI. Analisis mengacu pada Undang-Undang No.22 Tahun 2009. Berdasarkan hasil analisis data Kepolisian diperoleh 87,98% tipe pelanggaran di Surakarta berkaitan dengan perilaku pengemudi, sedangkan dari data primer diperoleh sebesar 48,32%. Kurangnya kesadaran akan tertib berlalu lintas menyebabkan pengemudi pengabaikan keselamatannya. Hal ini terlihat dari prosentase responden yang menjawab Ya lebih besar dari Tidak terjadi hampir pada semua tipe pelanggaran. Pelanggaran lalu lintas dapat menjadi faktor utama kecelakaan lalu lintas. Oleh karena itu, penerapan aturan yang ketat perlu dilakukan bagi yang melanggar, baik berupa hukuman denda atau penjara.


Metabolites ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 460
Author(s):  
Ulla T. Schultheiss ◽  
Robin Kosch ◽  
Fruzsina Kotsis ◽  
Michael Altenbuchinger ◽  
Helena U. Zacharias

Kidney diseases still pose one of the biggest challenges for global health, and their heterogeneity and often high comorbidity load seriously hinders the unraveling of their underlying pathomechanisms and the delivery of optimal patient care. Metabolomics, the quantitative study of small organic compounds, called metabolites, in a biological specimen, is gaining more and more importance in nephrology research. Conducting a metabolomics study in human kidney disease cohorts, however, requires thorough knowledge about the key workflow steps: study planning, sample collection, metabolomics data acquisition and preprocessing, statistical/bioinformatics data analysis, and results interpretation within a biomedical context. This review provides a guide for future metabolomics studies in human kidney disease cohorts. We will offer an overview of important a priori considerations for metabolomics cohort studies, available analytical as well as statistical/bioinformatics data analysis techniques, and subsequent interpretation of metabolic findings. We will further point out potential research questions for metabolomics studies in the context of kidney diseases and summarize the main results and data availability of important studies already conducted in this field.


2009 ◽  
Vol 5 (3) ◽  
pp. 121-124
Author(s):  
Mp Tully ◽  
A Vail ◽  
S Roberts ◽  
L Brabin ◽  
R McNamee

This is the third of four papers to be published in Research Ethics Review in 2009, that address methodological issues of relevance to research ethics committees. It focuses on three issues: the representativeness of study participants, the size of the study and data analysis. Differences between best practices in qualitative and quantitative research are highlighted. The paper argues that, while lack of representativeness may not be unethical, the ethical implications of unnecessary restrictions on eligibility should be considered by committees. Studies that are either too small or too big can pose problems. Research teams need to have the necessary competence to enable an appropriate analysis focused on the main objectives and interpreted in the context of the limitations of the study design.


2011 ◽  
Vol 13 (3) ◽  
pp. 320-327 ◽  
Author(s):  
Diana Lynn Woods ◽  
Janet C. Mentes

Over the last 10 years, interest in the analysis of saliva as a biomarker for a variety of systemic diseases or for potential disease has soared. There are numerous advantages to using saliva as a biological fluid, particularly for nurse researchers working with vulnerable populations, such as frail older adults. Most notably, it is noninvasive and easier to collect than serum or urine. The authors describe their experiences with the use of saliva in research with older adults that examined (a) osmolality as an indicator of hydration status and (b) cortisol and behavioral symptoms of dementia. In particular, the authors discuss the timing of data collection along with data analysis and interpretation. For example, it is not enough to detect levels or rely solely on summary statistics; rather it is critical to characterize any rhythmicity inherent in the parameter of interest. Not accounting for rhythmicity in the analysis and interpretation of data can limit the interpretation of associations, thus impeding advances related to the contribution that an altered rhythm may make to individual vulnerability.


2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Haiyin Huang ◽  
Jiaqi An ◽  
Lizhi Lu ◽  
Mingli Wang ◽  
Huijia Chen ◽  
...  

More and more scholars choose N-of-1 trials for TCM clinical research. However, the quality of the experimental designs was uneven. Accumulating more than eight years of experience in exploring the N-of-1 trials of TCM, the authors and their team searched the related literature in main Chinese and English databases, referenced to relevant Chinese and international guidelines. The design, implementation, and data analysis of N-of-1 trials of TCM are still in in-depth exploration and practice. “Carryover effect” may affect the design and quality of the trials. Individualized treatment should be guided by the classic theories of TCM. It is expected to formulate reasonable observation periods and pairs and closely integrate individual and group statistical analysis.


2020 ◽  
Vol 7 (1) ◽  
pp. 53-71
Author(s):  
Rachel E. Herring ◽  
Elisabet Tiselius

Abstract: Retrospective verbal process tracing is a popular research method in Interpreting Studies, employed by a growing number of scholars, particularly in studies of conference interpreting, but, to date, it has not been widely employed in studies of dialogue interpreting. This paper begins by introducing process-tracing methodologies, defining types of verbal process tracing, and presenting a brief critical review of publications employing this research methodology. The bulk of the article provides concrete, practical information and guidance for scholars of dialogue interpreting who are interested in employing retrospective process tracing in their research. We discuss the theoretical underpinnings of the method, methodological considerations that must be taken into account in the design and procedure of such studies, data analysis and reporting on the basis of retrospective process tracing, and recommendations for best practices.Resumen: El seguimiento retrospectivo verbal de procesos se utiliza cada vez más en los Estudios de Interpretación, sobre todo en la interpretación de conferencias. Con todo, este método se ha utilizado poco hasta la fecha en el campo de la interpretación bilateral. En la primera parte de este artículo, presentaremos los métodos de seguimiento de procesos, definiremos los tipos de seguimiento verbal de procesos y examinaremos brevemente algunos estudios que han empleado estos métodos. El objetivo principal es ofrecer recomendaciones concretas y prácticas que puedan resultar útiles para aquellos investigadores en interpretación bilateral que se interesen por estos métodos. Presentaremos las bases teóricas, las consideraciones metodológicas relevantes para el diseño y el procedimiento de tales estudios, el proceso de análisis y presentación de los datos obtenidos a través del seguimiento retrospectivo y algunas recomendaciones de buenas prácticas.


2020 ◽  
pp. injuryprev-2020-043987
Author(s):  
Liraz Fridman ◽  
Linda Rothman ◽  
Andrew William Howard ◽  
Brent E Hagel ◽  
Colin Macarthur

BackgroundThe global burden of MVC injuries and deaths among vulnerable road users, has led to the implementation of prevention programmes and policies at the local and national level. MVC epidemiological research is key to quantifying MVC burden, identifying risk factors and evaluating interventions. There are, however, several methodological considerations in MVC epidemiological research.MethodsThis manuscript collates and describes methodological considerations in MVC epidemiological research, using examples drawn from published studies, with a focus on the vulnerable road user population of children and adolescents.ResultsMethodological considerations in MVC epidemiological research include the availability and quality of data to measure counts and calculate event rates and challenges in evaluation related to study design, measurement and statistical analysis. Recommendations include innovative data collection (eg, naturalistic design, stepped-wedge clinical trials), combining data sources for a more comprehensive representation of collision events, and the use of machine learning/artificial intelligence for large data sets.ConclusionsMVC epidemiological research can be challenging at all levels: data capture and quality, study design, measurement and analysis. Addressing these challenges using innovative data collection and analysis methods is required.


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