If the colour codes change during the academic year to orange or red, modifications are possible, for example to the teaching and evaluation methods.

Course Code : | 1004GENGE2 |

Study domain: | Medicine |

Academic year: | 2020-2021 |

Semester: | 1st semester |

Sequentiality: | |

Contact hours: | 52 |

Credits: | 3 |

Study load (hours): | 84 |

Contract restrictions: | Faculty decision based on student file |

Language of instruction: | Dutch |

Exam period: | exam in the 1st and/or 2nd semester |

Lecturer(s) | Steven Abrams |

At the start of this course the student should have acquired the following competences:

an active knowledge of

specific prerequisites for this course

an active knowledge of

- Dutch

- English

- general knowledge of the use of a PC and the Internet

specific prerequisites for this course

The student has to have a basic knowledge about working with a computer. At the same time a basic knowledge of the English language is required because looking for information goes via international scientific publications which are most of the time written in English.

- 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 compare 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).
- Study aim 7: Make the difference between a random and systematic error and indicate which methods are used to avoid these errors in medical scientific research.
- Study aim 8: Define confounding and indicate that confounding is related to the study population.
- Study aim 9: Define effect modification and indicate that effect modification is related to the target (theoretical) population.
- Study aim 10: Indicate the difference between confounding and effect modification.
- Study aim 11: Formulate the diagnostic problem in terms of a probability in the present.
- Study aim 12: Formulate the prognostic problem in terms of a probability with a directionality in the future.
- Study aim 13: Formulate the etiognostic problem in terms of a probability in the present with a directionality in the past.
- Study aim 14: Describe the difference between descriptive and causal functions.
- Study aim 15: Formulate multiple linear, logistic and Cox proportional hazards models and indicate how effect modification in the form of an interaction term is introduced in such models.
- 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.
- Study aim 7:
- Study aim 8: Critical reflection with regard to confounding in medical scientific research and how it is addressed.
- Study aim 9: Interpret contradicting research results in the context of the potential presence of effect modification.
- Study aim 10: Translate medical problems in medical scientific research to appropriate statistical models.
- Study aim 11: Select and reflect on the study design for medical research.
- Study aim 12: Know the relationship between linear and logistic regression.
- Study aim 13: Know the relationship between Cox regression and Kaplan-Meier estimation in survival analysis.
- Study aim 14: Interpret the output for multiple regression analyses (linear, logistic, Cox) and translate this into the different effect measures.
- To applicate: Study aim 1: Working with statistical R software. Use simply statistical techniques on simple data sets from a medical environment (inclusive testing and estimation).
- 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.
- Study aim 6: Apply multiple regression techniques to solve diagnostic, prognostic and etiognostic problems.

General content:

- Introduction to epidemiology and medical statistics

Content epidemiology:

- 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
- Frequency of occurrence for events and states: prevalence, incidence and survival analysis
- Diagnosis: about cut-offs and prevalence functions
- Prognosis: interventional and descriptive prognostic research
- Etiognosis: causal functions
- Sources of error in medical scientific research
- Confounding and effect modification

Content medical statistics:

- Descriptive statistics: the presentation of results
- Inferential statistics: the reporting of simple and multiple associations
- Simple and multiple linear regression
- Multiple logistic regression
- Cox proportional hazards regression

Aims medical statistics:

- The student is able to apply simple statistical techniques to datasets.
- The student is able to apply definitions and mathematical formulas to solve probabilistic problems.
- The student is able to perform elementary statistical analyses with statistical R software.
- The student is able to interpret statistical output.
- The student is able to report about statistical analyses.
- The student is able to judge medical information/literature on validity and is able to assess critically whether the applied statistical methodology is appropriate, i.a. using principles from inferential statistics.

Class contact teachingLectures Practice sessions Seminars/Tutorials

Directed self-study

**5.3 Facilities for working students ***

Classroom activities

Directed self-study

Classroom activities

- Lectures: recording available via video link on Blackboard
- Exercise sessions: free to choose the group division
- Practica: free to choose the group division

ExaminationWritten examination without oral presentation Open book Multiple-choice Open-question

Continuous assessmentAssignments Participation in classroom activities

Continuous assessment

All documentation is online available (on Blackboard) for the student. No extra notes are required.

Fundamentals of Biostatistics, B. Rosner, 8th edition, Brooks Cole, ISBN: 978-1-305-2689-0

Essential Medical Statistics, R. Kirkwoord, J. A. C. Sterne, 2nd edition, Wiley-Blackwell, ISBN: 978-0-865-42871-3

Steven Abrams: Steven.Abrams@uantwerpen.be