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Objectives:
This series will provide you with tools to critically process and analyze medical scientific literature. You will get a good understanding of basic statistical concepts and theory that enable you to explain, understand and interpret data. These Webinars are practical and based on published articles and the analysis of these. You will work with the theory in practice to increase your understanding of the strengths and weaknesses of the statistics in scientific literature.
Statistical analysis in clinical trials
– Null/alternative hypotheses
– Statistical assumptions (type I error, significance level, type II error, statistical power,)
– Hypothesis testing
– Statistical tests
Statistics used in RCTs
– Type of outcome measures (dichotomous, continuous, time-to-event)
– Statistics used for analysis of dichotomous data (relative risk, odds ratio, risk difference, NNT)
– Analysis of time-to-event variables (plotting and interpretation of Kaplan-Meier curves)
