MSCI Biostatistics II Course Schedule -- February 2024

Key:
A = Whitlock and Schluter (text)
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

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 column below

Date		Room	Material to read/watch prior to class	Session Topics	Assignments	Examples
Thurs	1	Zoom	Course Webpage Syllabus Key Concepts Glossary A17.1-17.7, A17.10-1 B10-B10.5 H2.4.7	Simple Linear & Nonparametric Regression	Getting Started
	2	Zoom	A18, B10.6 B9.4-9.9	Multiple Linear Regression R rms Package	HW 1	abd17-lion: lion age from nose
Mon	5	Zoom	B10.7-10.10	"	HW 2
	6	Zoom	B13-13.6.1, 13.13	Analysis of Covariance in Randomized Studies	HW 3	abd18-molerats: mole rats
	7	Zoom	Hxiii, H1, H2-2.3.1, classification blog	Regression Modeling Strategies: Introduction	Exercise: ID the model Final project dataset in hand	abd18-molerats: chunk tests cat-pred: categorical predictors, taking control of contrasts
	8	Zoom	H2.3.2-2.4.1-2.4.6 demos	Methods for Multivariable Models	HW 4	splinex: polynomial and spline fitting
	9	Zoom	H2.4.8-2.7.2 (omit 2.5.1), 2.8	"	HW 5	support: nonlinear relationships
Mon	12	Zoom	H3, H4-4.1.2	Missing Data, Multivariable Modeling Strategies	HW 6 HW 7 (optional)	support: missing data nhgh: basic diagnostics
	13	Zoom	H4.3-4.7.2, 4.7.5-4.7.7	Variable Selection, Overfitting, Shrinkage, Collinearity, Data Reduction	HW 8	nhgh: data reduction support: variable clustering
	14	Zoom	H4.9-5.1.1, this	Influential Observations, Comparing Models, Improving Practice, Strategies, Describing the Fitted Model		nhgh
	15	Zoom	H5.1.2, 5.1.3, H5.2-5.4, (omit 5.5), B10.10	Performance Indexes, Relative Explained Variation, Bootstrap, Validation, Bootstrapping Ranks	HW 9	framingham: outliers framingham: internal validation
	16	Zoom	H5.6, B6.8, 6.9, 6.10-6.10.2, A17.9	Relative Effect Measures, Introduction to LRM	Prep for critique	Simple Logistic acath: binary logistic 2
	Mon	19	Zoom	Student led discussion of papers	HW 10	Final project statistical analysis plan finished
	20	Zoom	A17.9, H10-10.5, 10.8-10.10, NNT	Final project analysis file finished Binary Logistic Models, NNT
	21	Zoom	B6.10.3, B13.6.2-13.7, blog, blog, H11	" + Case Study		support: ordinal predictors
	22	Zoom	H12, HTE, HTE, B19, More Analyses of Diagnostic Yield, Simple Decision Analysis	Binary Logistic Model Case Study, Risk-based diagnostic research, ROC curves, HTE	HW 11	Bayes and this
	23	Zoom	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	Proportional Odds Ordinal Logistic Models	HW 12 (Optional) HW 13	simhiv: ordinal regression
Mon	26	Zoom	H17.1-17.3, 17.5.1, H18.1, 18.3-18.3.6, H20-20.1.5, 20.3, 20.7, H21	Survival Analysis Cox Model
	27	Zoom	B15, Advantages, Efficiency, H22	Analysis of Serial Measurements Ordinal Longitudinal Data
	28	Zoom	To be determined
	29	Zoom	Student Presentations of Final Project	Final Project

Biostat2Stata : Stata code for in-class examples, 2022