Learning line scientific training

Academic year: 2010-2011 Course code module BGEN-14 Semester: 2nd semester Credits: 3 Study load (hours) 84 Theory (hours): 30,00 Practice/Exercises(hours): 0,00 Other (hours): Part-time program: Instructor(s) Joost Weyler Language of instruction: Dutch Semester exam information: exam in the 2nd semester Contract restriction information: faculty decision 1. Prerequisites *Algemene competenties The student has to have a basic knowledge with working with a computer. At the same time a basic knowledge of the English language is expected because looking for information goes via international scientific publications which are most of the time written in English. *Sequentiality None all courses of Ba1 2. Objectives (expected learning outcomes) To know: Study aim 1. Name the essential elements of scientific nature (abstract, objective and rational). Understand the dangers of the use of absolute numbers when discussing frequency of occurrence. Give a definition for theoretical epidemiology. Name the different rubrics of scientific knowledge that is relevant for health. Study aim 2. Make the difference between the theoretical and research population. Define the binomial and normal distribution. Indicate the manner on which continuous, discrete and categorical features are summarized and presented. Indicate how the relation between these features is represented. To distinguish the convenient statistical techniques which allow to comparie means and proportions. Study aim 3. Making the difference between object design and methods design with a view of the conduct of medical scientific research. Indicate what the basis is of diagnostic, prognostic and etiognostic study objects. Write the basic form of a multiple linear regression. Distinguish the different habitual terms handled in the classification of research. Study aim 4. Identify the different measures of occurrence of disease (prevalence, cumulative incidence, incidence density). Define the concept ‘censored observation time’. Give the three reasons why an observation time can be censored. Formulate the aims of survival analysis.  Study aim 5. Make the difference between component and sufficient causes. To make the difference between induction time and latency period. Indicate the basic requirement for studying the effects of an exposure on the occurrence of events. Define the different measures of effect. Study aim 6. Reproduce the validation parameters of a diagnostic test. Note the basis form for a occurrence function (logistic regression).   To understand: Study aim 1. Indicate the general form of a study objects relevant for the domain of health and ill-health and to illustrate this on the basis of an original example. Study aim 2. Discuss critically the different usual terms handled in the classification of research. Indicate on which manner relevant temporal aspects can be taken into account. Study aim 3. The dangers of the use of absolute numbers in presenting frequency of events/states. Indicate the advantages and disadvantages of the different measures for the frequency of the occurrence of events. Indicate which problems are (partially) resolved by survival analysis. Discuss the concept of survival function. Discuss the concept of risk function. Study aim 4. Indicate that in the domain of health and ill-health mono causal processes are in advance rare. Develop a general model for causality. Explain conflicting results in studies on the relation between events and their determinants in different circumstances. Indicate on the basis of a model for (multi) causality under which condition the influence of a feature on the occurrence of events can be quantified. Study aim 5. Explain the elementary rules for calculating with probabilities and conditional probabilities on the basis of an example. Explain how the concept of ‘chance’ can be handled when translating (inferring) study results to ‘general’ (abstract) knowledge. Discuss the statistical techniques to determine the sample size that is necessary to conclude whether an expected medical effect is present or not. Make the difference between testing the nul-hypothesis and the estimating of a confidence interval. Study aim 6. Indicate how the determination of the presence of an illness is a matter of uncertainty. Reproduce and discuss a general model for the natural history  of disease. Indicate how the choice of a cut-off for dichotomising a diagnostic (continuous) feature is made. Explain the validity (parameters) of a diagnostic test. Indicate the draw-backs and limitations of the approach of the diagnostic problem via diagnostic tests and with this the frequently used technics based on the validity parameter and the application of Bayes’ theorem and which solution can be represented for this.   To applicate: Study aim 1. To use the informatics for setting up databases. Working with statistical computer packages. Use simply statistical techniques on simple data sets from a medical environment (inclusive testing and estimating). Study aim 2. Calculate the different measures of disease frequency (prevalence, cumulative incidence, incidence density). On the basis of a database to perform a simple survival analysis including the representing of an average survival time, an average hazard rate (h) or the incidence density (ID) and a survival curve (according to Kaplan-Meier). Study aim 3. The student is able to calculate and interpret a confidence interval for results of research like average and proportion, difference in average and difference in proportion. The student is able to test the nul-hypothesis  for a mean, a proportion, a difference in means, a difference in proportions by calculating and interpretation of a p-value. Study aim 4. Indicate the different discussed measures of association between the dependent and independent variables and calculate them in numerical examples. Quantify in simple exercises the effects of exposure in the different study forms . Study aim 5. Calculate the validity parameters of a diagnostic test. Calculate the predictive values of a test result underneath different disease frequency, via tabling, the theorem of Bayes or via the likelihood ratio. Develop a simple prevalence function in order to resolve a simply diagnostics problem. 3. Course content - Introduction to epidemiology and medical statistics - From research question over research object to research protocol: diagnosis, prognosis and   etiognosis - The relation between the theoretical population and the study population - Sampling and the consequential random error - Descriptive statistics: the presentation of test results - Frequency of occurrence for events and states: prevalence, incidence and survival analysis - Inferential statistics: the reporting of simple associations - Diagnosis: about cut-offs and prevalence functions - Prognosis: interventional and descriptive prognostic research 4. Teaching method Direct contact: Lectures Exercise sessions Tutorials Personal work: Supervised self-study 5. Assessment method Exam: Written, without oral presentation Multiple choice Practical exam Continuous assessment: (Interim) tests 6. Compulsory reading – study material All documentation is on-line available via electronic way for the student. No more extra notes are required. 7. Recommended reading - study material 8. Tutoring laatste aanpassing: last update: 14/01/2010 10:01 david.kums