MSCI Biostatistics II Detailed Course Schedule

February 2025

Key:

`A`	Analysis of Biological Data by Whitlock and Schluter
`B`	Biostatistics for Biomedical Research (handout); Some of the chapters include audio narration and video
`H`	Harrell (text) and the corresponding chapter in RMS Handouts
`Read`	Material to read/watch prior to class
`Assignment`	To do after the day’s material is covered
`Examples`	In-class examples

Homework assignments are here

To fetch scripts for in-class examples and copy them into the RStudio script editor pane:

Point to the RStudio command console (usually lower left pane)
Run require(Hmisc) to load the getRs function
Run getRs('xxx.qmd', put='rstudio') where the script file name xxx is replaced by the name given in the examples below

Feb 3: Class overview and simple linear regression
- Read
  - Course web page
  - Syllabus
  - Concepts
  - Glossary (read a few entries)
  - A17.1-17.7, A17.10-1, B10-B10.5, H2.4.7
- Assignment: Getting started (Zulip topic Course Information)
Feb 4: Multiple linear regression and the R rms package
- Read A18, B10.6, B9.4-9.9
- Assignment: HW1
- Example: abd17-lion: lion age from nose
Feb 5:
- Read B10.7-10.10
- Assignment: HW2
Feb 6: Analysis of covariance in randomized studies
- Read B13-13.6.1, 13.13
- Assignment: HW3
- Example: abd18-molerats: mole rats
Feb 7: Regression modeling strategies: introduction
- Read Hxiii, H1, H2-2.3.1, classification blog
- Final project dataset in hand
- Exercise: ID the model
- Examples:
  - abd18-molerats: chunk tests
  - cat-pred: categorical predictors, taking control of contrasts
Feb 10: Methods for multivariables models
- Read H2.3.2-2.4.1-2.4.6 and run these demos
- Assignment: HW4
- Example: splinex: polynomial and spline fitting
Feb 11: Methods for multivariable models
- Read H2.4.8-2.7.2 (omit 2.5.1), 2.8
- Assignment: HW5
- Example: support: nonlinear relationships
Feb 12: Missing data, multivariable modeling strategies
- Read H3, H4-4.1.2
- Assignment: HW 6, optional HW 7
- Examples:
  - support: missing data
  - nhgh: basic diagnostics
Feb 13: Variable selection, overfitting, shrinkage, collinearity, data reduction
- Read H4.3-4.7.2, 4.7.5-4.7.7
- Assignment: HW8
- Examples:
  - nhgh: data reduction
  - support: variable clustering
Feb 14: Influential observations, comparing models, improving practice, strategies, describing the fitted model
- Read H4.9-5.1.1, this
- Example: nhgh
Feb 17: Performance indexes, relative explained variation, bootstrap, validation, bootstrapping importance ranks
- Read H5.1.2, 5.1.3, H5.2-5.4, (omit 5.5), B10.10
- Assigment: HW9
- Examples:
  - framingham: outliers
  - framingham: internal validation
Feb 18: Relative effect measures, introduction to LRM
- Read H5.6, B6.8, 6.9, 6.10-6.10.2, A17.9
- Assignment: Prep for paper critique
- Examples:
  - Simple logistic
  - acath: binary logistic 2
Feb 19: Student-led discussion of papers
- Assignments:
  - HW10
  - Final project statistical analysis plan finished
Feb 20: Binary logistic models, NNT
- Read A17.9, H10-10.5, 10.8-10.10, NNT
- Assignment: Final project analysis file finished
Feb 21: Binary logistic models, case study
- Read B6.10.3, B13.6.2-13.7 (brief), blog, blog, H11
- Example: support: ordinal predictors
Feb 24: Binary logistic model case study, risk-based diagnostic research, ROC curves, HTE
- Read H12, HTE, HTE, B19, more analyses of diagnostic and prognostic yield, simple decision analysis
- Assignment: HW11
- Examples: Bayesian logistic model and this
Feb 25: Proportinal odds ordinal logistic models
- Read B4.1.2, B5.12.4-.5, power, B7.6-7.7, H13.1-13.3, 13.4.3, 13.4.5, 13.4.7, H14.1 and table 14.1, 14.2, H15-15.2, 15.5.2, Figure 15.15, 15.16
- Assignments:
  - HW12 (optional)
  - HW13
- Example: simhiv: ordinal regression
Feb 26: Survival analysis and Cox model
- Read H17.1-17.3, 17.5.1, H18.1, 18.3-18.3.6, H20-20.1.5, 20.3, 20.7, H21
Feb 27: Analysis of serial measurements
- Read B15, advantages, efficiency, H22
Feb 28: Student presentations of final projects