Summary of all the lectures and seminars of the module Design and Analysis of Biomedical Studies (Bachelor Biomedical Sciences, 2nd year). Samenvatting blok Design and Analysis of Biomedical Studies (DABS). De samenvatting bevat alle tentamenstof: uitgebreide en volledige aantekeningen van alle col...
Design & Analysis of Biomedical Sciences
3.1 LT Introduction to DABS 07/12/2020 – R. de Mutsert & S. Böhringer
Contact
- Any questions: B2BS@lumc.nl
- Support: S.P.Bamborough@lumc.nl (Stefanie Bamborough)
4-week course
- Jan 15 2021: examination April 26 2021: retake examination
o No books allowed, Remindo calculator allowed
- Info: syllabus, materials & daily overviews on Brightspace
Four central themes
1. Information Literacy and Data Management
2. Study Designs
3. Statistical Analysis
4. Interpretation of Results
Syllabus & Brightspace
- Topic numbers Brightspace match the topic numbers syllabus and time schedule
- According to four themes; independent from time schedule
Computer practicals
- Start with 30-min recap live in Kaltura
- Followed by computer practical
o Break-out rooms / own time
o Teachers are present in Kaltura for questions
o Reports including syntax file need to be uploaded to Brightspace
o Make sure you have a working version of SPSS on your computer
- Two students can work on a report together
o Each of the two students submits the same report using Turnitin
- All reports have to be submitted by the day of the exam
Examination
- Midterm test on Brightspace before Chrismas holidays
- Test exam after Christmas holidays in Remindo
- January 12: Response lecture statistical analysis & Question hour test exam
Final grade
- Examination: 100% of grade
- Combination of multiple choice and (5-7) open questions
- Will be published if obligated working groups attended and obligated reports uploaded to BS
,3 - Introduction to the course
3.2 LT Recap Epidemiology 07/12/2020 – R. de Mutsert & S. Böhringer
Research question: exposure/determinant, outcome, domain (study population) & time/period
Methods of epidemiological studies
Measures of disease frequency: describe how often a disease or another health event occurs in a
population
- Prevalence: number of subjects having the disease at a time point / total number of subjects
in population
o Number of existing cases / total population
o No information on new cases
o Important for planning of care and policy
- Incidence: amount of new cases
o Risk/incidence proportion: number of subjects developing the disease over a time
period / total number of subjects followed over that time period
New cases over time period / total population at risk followed
o Incidence rate: number of subjects developing the disease / total time at risk for the
disease for all subjects followed (person-time)
New cases / total time followed (person-years)
Population data (mortality rate, birth rate)
Epidemiological study designs
- Cross-sectional study (diagnosis)
o Determine determinant & outcome at one moment > prevalent cases
- Follow-up/cohort study (prognosis) > association between exposure & occurrence of disease
o Study population with subjects exposed (index) and non-exposed (control)
o Followed during time
o Count number of disease/with the outcome
- Case-control study (etiology) > association between exposure & disease
o Selection of patients with disease (cases)
o Ask about their exposure
o Compare their history of exposure with that of control persons without the disease
Exposure Odds Ratio
- Randomised controlled trial (RCT) (therapy) > effect and safety of intervention
o Experiment
o Randomisation of treatment and placebo
Measures of effect
- Relative risk (RR)
o Risk ratio = risk exposed / risk unexposed
o Rate ratio = incidence rate exposed / incidence rate unexposed
- Risk difference (RD) = risk exposed – risk unexposed
- Number needed to treat (NNT) = 1 / RD
o Number of patients that need to be treated to prevent one disease/death
- Odds ratio = odds cases / odds control
o Odds = exposed / non-exposed
o Estimation of RR
,
, Describing statistics
Categorical variables: summarized by counts (%)
- Ordinal: categorical, with specific order
- Nominal: categorical, no order
Numerical/continuous variables: summarized by mean (SD), median (SD) & quantiles (25%, 75%)
- All (positive) values possible & all steps equivalent
- Mean & standard deviation > outliers can have large influence on mean & SD
o Center of data: median (50% quantile)
o Variation: interquartile range (Q75 – Q25)
Analysing data
Standard deviation (SD): variation of single measurements
-
Standard error of the mean (SE): variation of the mean
-
- What would be the variation of the mean for many repetition of the experiment
- With a larger sample size SE becomes smaller
Confidence interval: determine whether an observed mean is larger than a given value
- Mean ± 1.96 SE
o For N > 30 (small sample sized; calculation inaccurate)
o Whether you can reject null hypothesis or not
Null hypothesis: opposite of what we want to show
P-value: chance to observe the data itself / even extremer data set, under the assumption that the
null hypothesis is true
- Conclusion about data (does it fit with null hypothesis?), no conclusion about null hypothesis
- Power: chance to reject the null hypothesis when it is true
- α-level: significance level, normally 5% (95% confidence level)
Required knowledge about statistics: Variables (1,4,5), Confidence intervals (10,11), null/alternative
hypothesis (17,18), P-values, power, independent/paired t-test (20,21), Contingency tables/Chi-
square test (24), Correlation (26) & Linear regression (27)
Research (UDEC) protocol
- UDEC = Universitair Dier Experimenten Commissie
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