Statistical Thinking in Biomedical Research | Schedule

Note: Measuring change is currently listed as a topic in both Sections 1 and 5. It will only be briefly discussed in Section 1.

The goal of the course is to present the biostatistical concepts that researchers need in order to evaluate the results of published clinical studies, to design and analyze studies, and to collaborate effectively with methodologists. The course will illustrate how biostatistical and epidemiologic principles affect all phases of the study, including choosing an outcome measure, developing procedures for collecting accurate and complete data and summarizing study results. Participants will be introduced to fundamental concepts in statistical inference and will learn to recognize the problems of bias and imprecision that can lead to misleading or uninformative results. Participants will also be introduced to the value as well as the limitations of statistical models. Participants will learn how to avoid misleading graphics and will see examples of the latest graphical methods for summarizing data accurately. The emphasis in the course is on the underlying concepts, not on computations.

The text for the course is Essential Medical Statistics, Second Edition by Betty R Kirkwood and Jonathan AC Sterne. In the required readings listed below, K&S refers to this book. Participants must read the chapters and articles marked required below before class, and they should review these materials again after class. Sections that are exceptionally important are marked in bold. Post questions about unresolved issues on the discussion board for the course, or bring them to class on which Section 7 is scheduled. Handouts should be printed before class and brought with you. Article titles that appear in color or are underlined have links to full text or abstracts.


Note: The order sections are presented may not correspond to what is below. The schedule is here.

Section Number Topic
1 Introduction to Statistical Concepts
2 Tools for Formal Statistical Inference
3 Statistical Modeling
4 Experimental Design and Analyzing Serial Measurements
5 Measuring Effects and Quantifying Evidence in Biomedical Research
6 Graphical Methods
7 Miscellaneous Issues and Demonstration of Statistical Software and Data Analysis
Topic revision: r7 - 07 Nov 2004, FrankHarrell

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