BIOSTATS 640 Intermediate Biostatistics Biostatistics and Epidemiology UMass Amherst

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For Students

1. Review of BIOSTATS 540
2. Discrete Distributions

3. Introduction to Nonparametrics

4. Categorical Data Analysis

5. Normal Theory Regression
6. Analysis of Variance

7. Logistic Regression
8. Introduction to Survival Analysis
9. (Time permitting) Introduction to Mixed Models

5. Normal Theory Regression

Scroll down for (1) BIOSTATS 640 2021 (2) Additional Readings and Videos (3) Resources for Learning R (4) Resources for Learning Stata, (5) Other (Applets, Calculators, etc.) and 6) Other Resources

(1) BIOSTATS 640 - 2021
UNIT INTRODUCTION
ppt INTRODUCTION (Source: Whitlock and Schluter ) Overheads 16 - Correlation (pdf, 6 slides)
ppt INTRODUCTION (Source: Whitlock and Schluter ) Overheads 17 - Regression (pdf, 12 slides)
ppt INTRODUCTION (Source: John McGready, JHSPH Methods in Biostatistics II) Simple Linear Regression (pdf, 19 slides)
ppt INTRODUCTION(Source: John McGready, JHSPH Methods in Biostatistics II) Linear Regresion - Motivating Examples (pdf, 23 slides)
(Source: www.artofstat.come) WebApps > Fit Linear Regression Model (html)
Lecture Notes - 2021 course notes, 5. Regression and Correlation Posted (pdf, 58 pp)
(janka.Rdata)
(p53paper.Rdata)
(framingham_1000.Rdata)

(p53paper_small.dta)
(framingham_1000.dta)

FAQ 1 - Schematic of Analysis of Variance (pdf, 2 pp)
FAQ - Incremental Sum of Squares, Analysis of Variance and Partial F-Tests (pdf, 2 pp)
FAQ - Confounding and Effect Modification (pdf, 6 pp)
BMTRY 701 Lecture 12 - Multiple Linear Model: Model Building (pdf, 24 slides)
(Source: Tindall, David, Department of Sociology, University of British Columbia) Regression Diagnostics Procedures (pdf, 31 slides)
Homework due Friday March 26, 2021
Last date for submission for credit (-20 points): Friday April 2, 2021
Questions (pdf, 6 pp)
SOLUTIONS to homework
R Users (pdf, 16 pp)
STATA Users (pdf, 15 pp)

Simple Linear Regression:
VIDEO (Source: OpenIntro - Simple Linear Regression) Line Fitting, Residuals, and Correlation (video, 4:05)
VIDEO (Source: OpenIntro - Simple Linear Regression) Inference for Linear Regression (video, 4:20)
(Source: BBaldi at WH Freeman, 2006) Looking at Data: Relationships (pdf, 12 pages, 23 slides)
(Source: JHSPH Open Course Ware Course - Statistical Reasoning II John McGready, Instructor)
Lecture 4a: Simple Linear Regression (pdf, 19 slides)
(Source: JHSPH Open Course Ware Course - Statistical Reasoning II John McGready, Instructor)
Lecture 4b: Linear Regression: Motivating Example (pdf, 23 slides)
(Source: JHSPH Open Course Ware Course - Statistical Reasoning II John McGready, Instructor)
Lecture 4c: Simple Linear Regression: More Examples (pdf, 21 slides)
(Source: JHSPH Open Course Ware Course - Statistical Reasoning II John McGready, Instructor)
Lecture 4d: Simple Linear Regression Model: Estimating the Regression Equation (pdf, 27 slides)
(Source: JHSPH Open Course Ware Course - Statistical Reasoning II John McGready, Instructor)
Lecture 4e: Measuring the Strength of a Linear Association (pdf, 23 slides)
(Source: JHSPH Open Course Ware Course - Statistical Reasoning II John McGready, Instructor)
Lecture 4f: Some FYI's about SLR (pdf, 11 slides)
(Source: Jeremy Balka's Statistics Channel - jbstatistics)
VIDEO: Introduction to Simple Linear Regression (video 8:09)
(Source: Jeremy Balka's Statistics Channel - jbstatistics)
VIDEO: The Least Squares Regression Line (video 7:24)
(Source: Jeremy Balka's Statistics Channel - jbstatistics)
VIDEO: Simple Linear Regression: Interpreting Model Parameters (video 5:05)
(Source: Jeremy Balka's Statistics Channel - jbstatistics)
VIDEO: Assumptions (video 3:05)
(Source: Jeremy Balka's Statistics Channel - jbstatistics)
VIDEO: Checking Assumptions with Residuals Plots (video 8:04)

Multiple Linear Regression:
VIDEO (Source: OpenIntro - Multiple Linear Regression) Introduction to Multiple Regression (video, 4:52)
(Source: Kari Lock Morgan, STATS 101) Multiple Regression (pdf, 41 slides)
(Source: John McGready, Johns Hopkins University) Statistical Interaction and Linear Regression (pdf, 37 slides, 7 pp)
(Source: JHSPH Open Course Ware Course - Statistical Reasoning II John McGready, Instructor)
Lecture 5a: Relating a Continuous Outcome to More Than 1 Predictor - Multiple Linear Regression (html)
(Source: JHSPH Open Course Ware Course - Statistical Reasoning II John McGready, Instructor)
Lecture 5b: More Examples (html)
(Source: JHSPH Open Course Ware Course - Statistical Reasoning II John McGready, Instructor)
Lecture 5c: Variability in Multiple Linear Regression: Assessing Linearity and Goodness of Fit (html)
(Source: JHSPH Open Course Ware Course - Statistical Reasoning II John McGready, Instructor)
Lecture 5d: Handling Multiple Categorical Predictors in Multiple Linear Regression (html)
(Source: JHSPH Open Course Ware Course - Statistical Reasoning II John McGready, Instructor)
Lecture 6a: More Multiple Linear Regression (html)
(Source: JHSPH Open Course Ware Course - Statistical Reasoning II John McGready, Instructor)
Lecture 6b: More Details About Multiple Linear Regression. See especially pp 24-36 (html)
Multiple Linear Regression
(Source: courses.washington.edu/b515/l7) Lecture 7 - Linear Regression Diagnostics (pdf, 40 slides)
Multiple Linear Regression
(Source: courses.washington.edu/b515/l8) Lecture 8 - Regression Diagnostics - continued (pdf, 28 slides)
Multiple Linear Regression
(Source: courses.washington.edu/b515/l9) Lecture 9 - Variable Selection (pdf, 38 slides)

(3) Resources for R Learners
(source: Whitlock and Schluter, The Analysis of Biological Data, Third Edition) Labs Using R: 11. Correlation and Regression (html)
(Source: www.r-tutor.com R Tutorials) Simple Linear Regression (html)
(Source: Denise Ferrari, Vanderbilt) Regression in R (pdf, 96 slides)
(Source: Steiger J. Vanderbilt University) Introduction to Multiple Regression (pdf, 54 slides)
(source: BIOSTATS 690C Fall 2020) Illustration: R for Simple Linear Regression (pdf, 11 pp)
(source: BIOSTATS 690C Spring 2021) Illustration: R for Multiple Linear Regression (pdf, 11 pp)
VIDEO
Simple Linear Regression

(Source: Christoph Scherber, University of Gottingen) Statistics with R (1) - Linear Regression (video, 19:21 min)
Multiple Linear Regression
(Source: Oscar Torres-Reyna, Princeton University) Getting Started in Linear Regression Using R (pdf, 24 pp)
Multiple Linear Regression
(source: UCLA Institute for Digital Research and Education - Statistical Consulting) Introduction to Regression in R (html)
Lesson 1. Simple and Multiple Regression (html)
Lesson 2. Regression Diagnostics (html)
Lesson 3. Regression with Categorical Predictors (html)
Multiple Linear Regression
(Source: www.statmethods.net) Quick R - Multiple Linear Regression (html)
(Source: Elizabeth Garret-Mayer, Medical University of South Carolina) RBMTRY 701
Lecture 3 - Simple Linear Regression: Introduction (pdf, 38 slides)
Lecture 4 - Simple Linear Regression Inferences and Diagnostics (pdf, 50 slides)
Lecture 12 - Model Building (pdf 24 slides)

(4) Resources for Stata Learners
(Source: Alicia Doyle Lynch, MIT/Harvard) Regression in Stata (pdf, 55 slides)
(Source: Stigum H. folkehelseinstituttet) Linear Regression: Birthweight by Gestational Age (pdf, 36 slides)
Illustration - Simple & Multiple Linear Regression (pdf, 27 pp)
(Source: UCLA Academic Technology Services) For STATA Users: Chapter 1 - Simple and Multiple Regression (html)

(Source: UCLA Academic Technology Services) For STATA Users: Chapter 2 - Regression Diagnostics (html)
(Source: StataCorp LP Youtube Channel - Chuck Huber)
VIDEO: Simple Linear Regression in Stata (video 5:15)
Illustration (quite nice!) of Some Basic Group Comparisons and Linear Regression
(Source: Klaus K. Holst, University of Copenhagen) Statistics in Stata: Quantitative Data, Group Comparisons and Linear Regression (pdf, 17 pp)
Illustration of Simple and Multiple Linear Regression
Multiple Linear Regression
(Source: Oscar Torres-Reyna, Princeton University) Linear Regression in Stata, 46 pp - a very helpful worked example in Stata (html)
Multiple Linear Regression
(Source: UCLA Department of Statistics - Statistical Consulting Center) Stata Web Books - Regression with Stata (html)
Chapter 1 - Simple and Multiple Regression (html)
Chapter 2 - Regression Diagnostics (html)
Chapter 3 - Regression with Categorical Predictors (html)

(5) Other Resources
(Source: Stat Trek AP Statistics) Statistics Tutorial: Least Squares Linear Regression (html)
(Source: Stat Trek AP Statistics) Statistics Tutorial: Correlation and Linearity (html)
(Source: Gerstman BB. Basic Biostatistics Statistics for Public Health Practice) Chapter 15: Multiple Linear Regression (pdf, 24 slides)
(Source: Mallick BK STAT 651) Lecture 20 (pdf, 43 slides)
(Source: I'm not sure, sorry! - Biometry 755 Spring 2009) Regression Diagnostics (pdf, 24 slides)
SPSS (Source: UCLA Academic Technology Services) Introduction to Regression with SPSS (html)
SAS (Source: UCLA Academic Technology Services) SAS Web Books Regression with SAS (html)

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 Copyright 2021 University of Massachusetts, Amherst. This is the course web site for BIOSTATS 640, Biostatistics Program, Department of Biostatistics and Epidemiology. Produced and maintained by the School of Public Health and Health Sciences. Send comments or questions about this web site to cbigelow@schoolph.umass.edu. Page updated: March 15, 2021