Biostatistics analyses with R
Programme
Pre-processing
- Workflow
- Using RStudio
- Using RStudio projects
- Using a simple files organisation method
- Data management:
- Import csv dataset, check and validate
- subsetting dataset with dplyr package
Descriptive statistics:
- variables type (numeric, factor) and their univariate and bivariate graphic representation
- position parameters
- dispersion parameters
Estimation
- principle
- sampling
- sampling fluctuation
- confidence interval
- bias
Principle of Hypothesis Test
- Null and alternative hypothesis
- alpha error risk
- pvalue
- power and sample size calculation
Comparing a sample parameter to a reference parameter
Comparing two samples
- comparing two means (independent samples)
- comparing two proportions (independent samples)
- comparing two means (paired samples)
- comparing two proportions (paired samples)
- comparing more than two proportions (independent samples)
Comparing more than two means (independent sample)
- ANOVA one way
- Kruskal Wallis test
- multiple comparisons
Comparing more than two means (paired samples)
- mixed models (hierarchical model)
- Friedman test
- multiple comparisons
Assessing link between variables
- two numeric variables
- correlation
- simple linear regression
- two quantitative variables
