This document contains an extensive summary of the lectures given in the course Biology of vitality and ageing as a part of the minor and master "Vitality and ageing" at leiden university.
Randomization
Random allocation takes away the bias of the doctor and
can thereby not influence the representativeness of the
population.
Double-blind
The evaluator assessing the patient for the outcome does
not know the treatment assignment AND The patient does
not know the treatment assignment
Eliminate effects of compliance, endpoint evaluation,
placebo effect, etc.
Control group
allows for better blinding and reduces risk of placebo
effect
Frequency and effect measures
Prevalence: the proportion of a population to be affected
by a condition at a given time
Consider a population of size N and suppose that P
individuals in the population have disease at a given time. The prevalence proportion = P/N
Cumulative incidence (risk/probability): the probability that a person will develop a given disease
Risk = (A = Number of subjects developing disease during a time period) / (N = Number of subjects at
baseline)
- Proportion, fraction
- 01
- Time specification is necessary
- (Absolute) Risk
, - Complete follow‐upup
Incidence rate (incidence density): the number of new cases per population at risk in a given period
Incidence rate = (A = Number of subjects developing disease) / (Time = Total time experienced for the
subjects followed)
- Density, not a proportion
- 0 infinity
- Unit person‐upyears
- Risk estimation only indirectly
- Loss to follow‐upup possible
Odds ratio
= probability the event will happen / probability it will not happen
= Probability / (1‐upProbability)
= (I1/(1‐upI1)) / (I0/(1‐upI0))
I = Incidence or prevalence
Risk difference = (a/N+) – (b/N‐up)
Risk ratio = (a/N+) / (b/N‐up)
Odds ratio = ((a/N+)/(c/N+) / ((b/N‐up)/d/N‐up)) = (a/c) / (b/d) = (a * d) / (b * c)
Number needed to treat
Number of patients that need to be treated (exposed) to prevent one outcome
1 / risk difference = 1 / (CI exposed – CI non ‐upexposed)
STATISTICAL ANALYSES
Numerical data for 2 independent groups
Unpaired t-test when normally distributed
Mann Whitney U test when not normally distributed
Paired vs unpaired
Paired --> compare same measurement of same group at different times eg
Independent --> compare same measurement between independent groups.
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