We simplify biostatistics for medical professionals and students—making complex methods clear, practical, and clinically relevant. Through easy-to-follow explanations, intuitive visuals, and essential math, we bridge the gap between statistics and medical research.
Types of research
Research can roughly be divided into the following types:
Descriptive Analysis: To summarize the data set without interpretation.
Exploratory Analysis: To find patterns, trends, or relationships to generate hypotheses.
Inferential Analysis: To estimate how findings in a sample hold for a larger population.
Predictive Analysis: To predict outcomes for individuals based on features.
Causal Analysis: To estimate what happens on average when one variable changes another (e.g. average treatment effect).
Mechanistic Analysis: Typically to establish how one variable deterministically influences another.
We will focus on the following on two aspects:
Interpretation and use of statistical evaluation measures
Pseudo R2 measures
Calibration
the 3 archetypical statistical models
Logistic regression
Linear regression
Cox regression
Extensions:
Extensions logistic regression
Ordinal logistic regression with proportional odds assumption
Extensions linear regression
Extensions Cox regression
References:
Leek, J., & Peng, R. D. (2015, February 26). What is the question? Science. https://doi.org/10.1126/science.aaa6146
Kiefer, J. C. (1987). Introduction to statistical inference (G. Lorden, Ed.). Springer.