CLRES 2020
BIOSTATISTICS: STATISTICAL APPROACHES IN CLINICAL RESEARCH
Summer 2010
COURSE DESCRIPTION
This course focuses o...
CO-INSTRUCTORS
Doug Landsittel, PhD
Associate Professor
Department of Medicine
University of Pittsburgh
200 Meyran Avenue,...
Trainees should choose 1 of the following 4 sessions and stay in the same session throughout of
the term.
Session A1: T, T...
Highly recommended books for Stat component of the course
Hamilton LC. Statistics with Stata (Updated for Version 10). Dux...
ACADEMIC INTEGRITY
Trainees in this course will be expected to comply with the University of Pittsburgh's Policy on Academ...
COURSE SCHEDULE (CLRES 2020, Summer 2010)
Date Lecture Rosner Instructor
7/7 (Wed) Lecture 1: Introduction to Biostatistic...
8/2 (Mon) Midterm Lectures 1 – 9 Chang
8/2 (Mon) Lab 4: Hypothesis Testing TAs
8/4 (Wed) Lecture 10: Sample Size and Power...
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CLRES 2020 BIOSTATISTICS: STATISTICAL APPROACHES IN CLINICAL ...

  1. 1. CLRES 2020 BIOSTATISTICS: STATISTICAL APPROACHES IN CLINICAL RESEARCH Summer 2010 COURSE DESCRIPTION This course focuses on basic concepts and methods of statistics and their application to problems in the health and biomedical sciences. Topics include graphical and numerical descriptions and summarization of data, basic probability theory, probability distributions, point and confidence interval estimation, and hypothesis testing with emphasis on one- and two-sample comparisons involving continuous and categorical data. Correlation, simple linear regression, and analysis of variance will be introduced. Scholars will work with clinical datasets and will learn to analyze the data and explain their findings. This rigorous first course in biostatistics will serve as a prerequisite for other biostatistics courses. COURSE OBJECTIVES At the completion of the course, the trainees should: know the basic statistical procedures used to analyze data; be able to apply these techniques utilizing a standard statistical package; appreciate the concepts of random variation and bias; appreciate the wide range of applications of biostatistical methods to problems in medicine and public health; know some specific applications in a specialized area of interest; and recognize pitfalls in interpreting biomedical and public health data. INSTRUCTOR AND COURSE DIRECTOR (Joyce) Chung-Chou H. Chang, PhD Associate Professor Department of Medicine University of Pittsburgh 200 Meyran Avenue, Suite 200 Pittsburgh, PA 15213 Tel: 412-692-4868 Fax: 412-246-6954 Email: changj@pitt.edu
  2. 2. CO-INSTRUCTORS Doug Landsittel, PhD Associate Professor Department of Medicine University of Pittsburgh 200 Meyran Avenue, Suite 200 Pittsburgh, PA 15213 Tel: 412-864-3019 Fax: 412-586-9672 Email: landsitteldp@upmc.edu Charity G. Moore, PhD Associate Professor Department of Medicine University of Pittsburgh 200 Meyran Avenue, Suite 200 Pittsburgh, PA 15213 Tel: 412-246-6961 Fax: 412-586-9672 Email: moorecg@upmc.edu TEACHING FELLOWS Jonathan Yabes, MS Department of Biostatistics University of Pittsburgh Tel: TBA Email: jgy2@pitt.edu Office hours: Thur 1-3pm Xinxin Dong, MS Department of Biostatistics University of Pittsburgh Tel: TBA Email: xid11@pitt.edu Office hours: Tue 10am-noon Elan D. Cohen, MS Center for Research on Health Care Data Center University of Pittsburgh Tel: 412-864-3014 Email: cohened@upmc.edu Office hours: Wed, Fri noon-1pm Yingda Jiang, MS Department of Biostatistics University of Pittsburgh Tel: TBA Email: yij5@pitt.edu Office hours: Fri 1-3pm MEETING TIMES & LOCATION July 7 – August 27, 2010 Lecture MWF 10:30am – 12noon Suite 305A/B, Parkvale Building (200 Meyran Avenue) Recitation
  3. 3. Trainees should choose 1 of the following 4 sessions and stay in the same session throughout of the term. Session A1: T, Th 8:30 – 10:00am, Suite 305A, Parkvale Building Session A2: T, Th 8:30 – 10:00am, Suite 305B, Parkvale Building Session A3: T, Th 8:30 – 10:00am, Suite 222, Parkvale Building Session B1: T, Th 3:30 – 5:00pm, Suite 305A, Parkvale Building Lab Trainees should choose 1 of the following 2 sessions and stay in the same session throughout of the term. Session A: M 1:00 – 5:00pm, Suite 305A/B, Parkvale Building Session B: M 1:00 – 5:00pm, Suite 222, Parkvale Building CREDITS 4 credits (64 contact hours/week for 8 weeks) GRADING Letter grade based on 30% Best 13 of 16 homework assignments 5% Lab assignments 25% Midterm examination (in class) 30% Final examination (in class) 10% Class participation TEXTBOOK Rosner B (2006). Fundamentals of Biostatistics, 6th Edition. Duxbury Press, Pacific Grove, CA. Also recommended (optional): Glover TJ and Mitchell KJ (2008). An Introduction to Biostatistics, 2nd Edition. Waveland Press Inc, Long Grove, IL. van Belle G, Fisher LD, Heagerty PJ, and Lumley TS (2004). Biostatistics: A Methodology for the Health Sciences, 2nd Edition. Wiley, New York. Daniel WW (2004). Biostatistcs: A Foundation for Analysis in the Health Sciences, 8th Edition. Wiley, New York. Everitt BS (2009). Modern Medical Statistics: A Practical Guide. Wiley, New York. COMPUTING PACKAGE Stata 11, Stata Press, College Station, Texas (www.stata.com) We recommend that students purchase or have ready access to this program. It can be purchased through www.stata.com. University of Pittsburgh does have a Stata “Grand Plan” available so the cost is reduced to students in this course. Stata is available at the course computer labs, at the Posvar Hall, and at the Falk library in Scaife Hall. For details, please click Software Info in the manual box on the left.
  4. 4. Highly recommended books for Stat component of the course Hamilton LC. Statistics with Stata (Updated for Version 10). Duxbury Press, Pacific Grove, CA SOFTWARE INFORMATION You will need to have access to a computer, a printer and specific statistical software to do the homework in the statistics courses. There are two statistics programs needed to do your homework in the statistics course. SSttaaTTaabbllee StaTable provides interactive way to calculate probability values and/or critical values for the twenty-five most commonly used statistical distributions. The software can be downloaded from the web with no additional charge. How to download StaTable from the internet Connect to the Internet. Go to www.cytel.com/. Select Software on the menu bar and choose StaTable from the menu bar on the left. Follow the instructions. On the right hand side of the new screen, you can choose Download StaTable for Windows or Download StaTable user manual. SSttaattaa 1111 Stata 11 can be accessed from our course computing lab, the University computer labs at Posvar Hall, or the Falk Library at Scaife Hall. Stata 11 can also be purchased via GradPlans. In the past we have recommended that students purchase Stata/IC (Intercooled Stata) with PDF documentation ($179). This is the best if you are planning to do multivariable modeling or intensive analyses when you are finished with this course. If your plans are for small studies and for statistics modules CLRES 2021 (Regression and ANOVA) and CLRES 2022 (Logistic Regression) only, student version of Stata/IC 11 with PDF documentation and one-year license ($98) or student version of Small Stata 11 with PDF documentation and one-year license ($49) will be sufficient. If you are buying only Small Stata and the Getting Started Manual, you will need to purchase the Statistics with Stata (Updated for Version 10) textbook as a reference. If you have decided to purchase Stata it is best to have it in your computer by July 15. (See instructions below). Important numbers/locations for Stata GradPlans at Pitt How to order Stata Go to http://www.stata.com/info/order/new/edu/gradplans/gp3-order.html. You can purchase Stata with a purchase order, a university p-card or your credit card. In some cases you may be able to get your department/ grant to pay for software. Ms. Jennifer Holliman can also help you order the software. Contact her (hollimanjl@upmc.edu or 412-586-9673) if you need assistance. Stata is also available for Mac and Linux machines. Make sure you specify the platform you are using when you order the programs.
  5. 5. ACADEMIC INTEGRITY Trainees in this course will be expected to comply with the University of Pittsburgh's Policy on Academic Integrity. Any trainee suspected of violating this obligation for any reason during the semester will be required to participate in the procedural process, initiated at the instructor level, as outlined in the University Guidelines on Academic Integrity. This may include, but is not limited to, the confiscation of the examination of any individual suspected of violating University Policy. Furthermore, no trainee may bring any unauthorized materials to an exam, including dictionaries and programmable calculators. DISABILITIES If you have a disability that requires special testing accommodations or other classroom modifications, you need to notify both the instructors and the Disability Resources and Services no later than the 2nd week of the term. You may be asked to provide documentation of your disability to determine the appropriateness of accommodations. To notify Disability Resources and Services, call 412-648-7890 (Voice or TTD) to schedule an appointment. The Office is located in 216 William Pitt Union. COPYRIGHT NOTICE These materials may be protected by copyright. United States copyright law, 17 USC section 101, et seq., in addition to University policy and procedures, prohibit unauthorized duplication or retransmission of course materials. See Library of Congress Copyright Office and the University Copyright Policy. OTHER LINKS CLRES 2005: Computer Based Data Analyses Clinical Research Training Program University of Pittsburgh Last updated: June 22, 2010
  6. 6. COURSE SCHEDULE (CLRES 2020, Summer 2010) Date Lecture Rosner Instructor 7/7 (Wed) Lecture 1: Introduction to Biostatistics Ch 1 – 2 Chang Homework #1 7/9 (Fri) Lecture 2: Probability Concepts I Ch 3 Chang Homework #2 Homework #1 due 7/12 (Mon) Lecture 3: Probability Concepts II and Bayes’ Theorem Ch 3 (continue) Chang Homework #3 7/12 (Mon) Lab 1: Descriptive Statistics and Probability TAs 7/14 (Wed) Lecture 4: Discrete Probability Distributions Ch 4 Chang Homework #4 Homework #2 and #3 due 7/16 (Fri) Lecture 5: Continuous Probability Distributions Ch 5 Chang Homework #5 Homework #4 due 7/19 (Mon) Lecture 6: Estimation I & Sampling Distributions Ch 6 Chang Homework #6 7/19 (Mon) Lab 2: Probability Distributions TAs 7/21 (Wed) Lecture 7: Estimation II Ch 6 (continue) Chang Homework #7 Homework #5 and #6 due 7/23 (Fri) Lecture 8: Hypothesis Testing: One-Sample Inference Ch 7 Chang Homework #8 Homework #7 due 7/26 (Mon) Lecture 9: Hypothesis Testing: Two-Sample Inference Ch 8 Chang Homework #9 7/26 (Mon) Lab 3: Estimation and Hypothesis Testing TAs 7/28 (Wed) Review I Midcourse review Chang Homework #8 and #9 due 7/30 (Fri) Review II Midcourse review Chang Week1Week2Week3Week4
  7. 7. 8/2 (Mon) Midterm Lectures 1 – 9 Chang 8/2 (Mon) Lab 4: Hypothesis Testing TAs 8/4 (Wed) Lecture 10: Sample Size and Power §7.6, §8.11 Moore Homework #10 8/6 (Fri) Lecture 11: Estimation and Inference for Categorical Data I Ch 10 Moore Homework #11 Homework #10 due 8/9 (Mon) Lecture 12: Estimation and Inference for Categorical Data II Ch 10 (continue) Moore Homework #12 8/9 (Mon) Lab 5: Sample Size/Power, Categorical Data and Contingency Tables TAs 8/11 (Wed) Lecture 13: One-way Analysis of Variance Ch 12 Chang Homework #13 Homework #11 and #12 due 8/13 (Fri) Lecture 14: Correlation and Simple Linear Regression I Ch 11 Chang Homework #14 Homework #13 due 8/16 (Mon) Lecture 15: Correlation and Simple Linear Regression II Ch 11 (continuous) Chang Homework #15 8/16 (Mon) Lab 6: Analysis of Variance, Correlation, and Simple Linear Regression TAs 8/18 (Wed) Lecture 16: Nonparametric Analysis Ch 9, §11.12, §12.7 Chang Homework #16 Homework #14 and #15 due 8/20 (Fri) Lecture 17: Logistic Regression Analysis Overview Landsittel Homework #16 due 8/23 (Mon) Lecture 18: Survival and Correlated Data Analysis Overview Landsittel 8/23 (Mon) Lab 7: Nonparametrics; Review TAs 8/24 (Tue) Review I Course review Chang 8/25 (Wed) Review II Course review Chang 8/27 (Fri) Final Exam Lectures 10 – 18 Chang Week5Week6Week7Week8

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