Explores robust regression in genomic data analysis, focusing on downweighting large residuals for improved estimation accuracy and quality assessment metrics like NUSE and RLE.
Explores the challenges of multiple testing in genomic data analysis, covering error rate control, adjusted p-values, permutation tests, and pitfalls in hypothesis testing.
Covers the principles and tools for reproducible research in biostatistics, emphasizing the importance of complete documentation and the use of text editors for compiling source documents.
Introduces the Cox proportional hazards model for survival analysis, covering estimation, assessment of assumptions, and interpretation using residuals.
