SMPE/e-‐cursus “Medische Statistiek en BioStatistische DataAnalyse” 30 October, 7+14+21+28 November, 12 December 2014. In de afgelopen jaren is het gebruik van statistische methoden bij het analyseren van beschikbare (onderzoeks-‐) gegevens enorm toegenomen. Dankzij statistische software zoals SPSS of R zijn deze methoden binnen het bereik van vrijwel iedere onderzoeker gekomen. Echter, voor de gebruiker van deze software is het niet altijd even duidelijk hoe de zo beschikbare methoden op verantwoorde wijze toegepast kunnen worden bij het oplossen van specifieke onderzoeksvragen uit adequaat opgezette experimenten of klinische studies. De SMP/e-‐cursus ‘Medical Statistics and Biostatistical Data Analysis’ speelt hier op in door een aantal gangbare methoden voor het analyseren van experimentele data te behandelen en inzicht te geven in de achterliggende principes. Tijdens de cursus is er aandacht voor het gebruik van statistische software voor het analyseren van data, terwijl deelnemers de gelegenheid hebben om hier zelf praktische ervaring mee op te doen. Ook wordt ingegaan op de manier om verkregen resultaten adequaat te rapporteren. Extra informatie: • • • • • • • doelgroep: klinisch fysici (i.o.) en andere technologie professionals in de zorg; interactieve cursus [3 ECTS]; data 2014: 30 October, 7+14+21+28 November, 12 December 2014. deze cursus wordt door SMPE/e jaarlijks aangeboden; lokatie: SMPE/e, TU/e, Eindhoven; kosten: €1600,-‐ (incl. lunches) maximaal aantal deelnemers: 20 (VOL ≡ VOL). Voor programma en meer info: www.smpee.tue.nl → courses Meer info en aanmelding: [email protected] (tel. 040 247 5897) Bijlage (1 blz.) Bijlage SMPE/e-course Medical Statistics & Biostatistical Data Analysis 30 October, 7+14+21+28 November, 12 December 2014. Course Description The course “Medical Statistics and Biostatistical Data Analysis” provides insight into the fundamentals of medical statistics and its application to clinical trials and experiments in healthcare, as relevant for post-graduate training and continuing education of medical physicists and other technology professionals in health care. Theory is supported by hands-on training sessions with practical exercises and class-room case studies, using relevant and easy to use statistical software such as SPSS. For successful completion of the course, participants have to prepare, present and discuss a case study which is relevant for their project or hospital. Goal: to teach the medical physicist and other technology professionals in health care the skills to design an adequate and efficient experiment or clinical trial. Starting out from a specific research objective, we supply the tools for analysis, discussion and to-the-point reporting of the results. Target groups • medical physicists (in training). • other technology professionals in health care. Qualification Standards After completion of the course, participants have a toolbox to design an adequate and efficient experiment or clinical trial and analyse and discuss the results obtained, starting out from a well defined research objective, Based on insight, a choice is made for the correct application of linear, non-linear, logistic, Poisson, or survival data regression models. Fitting these models to available data, checking the underlying assumptions and interpreting the results obtained are all part of the newly acquired skills. Other tools discussed are the application of one-way and factorial ANOVA for randomised groups and repeated measures. This includes the skills to fit these models to available data, check the underlying assumptions and interpret the results obtained including multiple comparisons methods and contrasts. The principles of blocking and sample size determination are discussed and applied in an adequate way. After a successful graduation from the course, the participants can apply statistical software in a proper way for the design and analysis of experiments and understand the underlying theory. Entry Requirements Basic knowledge of descriptive statistics, definition of probability, probability distributions, and concepts of testing and parameter estimation. At the start of the course, these concepts will be reviewed. Practical Training The course provides a fundamental understanding of stochastic ('random') quantities and discusses methods for statistical analysis and interpretation of data. We review statistical inferential methods such as testing and estimation for one-sample and two-sample cases, both parametric and non-parametric. Central in the approach is the planning and design of experiments and clinical trials and the modelling and analysis of the data obtained through regression and ANOVA models. Multiple linear and non linear regression, logistic regression, Poisson regression and hazard regression for the analysis of survival data will be discussed, as will be one-way and factorial ANOVA for randomized groups and for repeated measures. Also attention will be paid to multiple comparisons, contrasts and non-parametric methods, such as the Kruskal-Wallis and the Friedman test. Finally,we discuss the analysis of categorical data and aspects of blocking, fractioning and sample size determination. Examples are taken from Biostatistical practice. Literature: Obligatory (copy will be supplied at the start of the course). • Dupont, William D., Statistical Modeling for Biostatistical Researchers, 2nd edition (2009) ISBN 978-0-521-61480-1. Suggested reading: • Rosner, Bernard, Fundamentals of Biostatistics, 7th ed., ISBN 978-0-538-73589-6 • Landau, Sabine and Brian S. Everitt, A Handbook of Statistical Analyses using SPSS, ISBN 1-58488 (e-book available for TU/e-participants through VUBIS) Software: For illustrative purposes the statistical software package IBM-SPSS (preferably version 19, though versions 17 and higher will be OK!) will be used throughout the course. TU/e participants can install SPSS directly from: http://w3.tue.nl/en/services/dienst_ict/services/services_wins/campussoftware/spss/ External participants should check availability of IBM-SPSS from their own institution. If there is no licence available, they should inform the SMPE/e secretariat no later than October 7th (e-mail: [email protected]) so an adequate solution can be arranged in time. Participants are encouraged to bring in their own laptop during the course! Extra information • 3 ECTS. • This course will be given on a yearly basis. Those who are interested are asked to contact the SMPE/e-office, [email protected], as with enough candidate participants an extra course can be arranged upon request. • Type of examination: report, presentation and discussion on the (statistical) analysis of a representative case study. Lecturer: Dr. J.J.M. Rijpkema (course coordinator), TU/e – Department of Mathematics and Computer Science
© Copyright 2024 ExpyDoc
