The Biostatistics Collaboration Center (BCC) and the Outcomes Measurement and Survey Corein the Northwestern University Feinberg School of Medicine will be offering a series of 6 free introductory lectures on biostatistics in medical research. The lectures will be non-technical and have been designed with the following objectives:
- To assist participants in interpreting statistics published in the medical literature.
- To highlight different statistical methodology for investigators considering their own research.
- To facilitate the communication between medical researchers and biostatisticians.
The lectures are FREE and open to interested members of the Northwestern community! Registration is NOT required. Seating is available on first come basis. Lectures are 1 hour in length followed by a Q&A session. Lecture slides will be available to view and download one week prior to each lecture.
All lectures will be held in Lurie Hughes Auditorium at 303 E Superior Street from 12:00-1:00pm.
Tuesday, October 4th 12:00 – 1:00 PM
#1 – Basic Concepts
- Assist participants in interpreting statistics published in medical literature
- Highlight different statistical methodology for investigators conducting own research
- Facilitate communication between medical investigators and biostatisticians
Tuesday, October 11th 12:00 – 1:00 PM
#2 – Two Group Comparisons
- t-tests for paired and unpaired data
- nonparametric alternatives to t-tests
- comparing categorical variables between two independent groups
- comparing categorical variables between two paired groups
- chi-squared test
- nonparametric alternatives to chi-squared tests
- computing agreement between two groups on a continuous or categorical variable
- power computations for two group comparisons
Tuesday, October 25th 12:00 – 1:00 PM
#3 – Introduction to Linear Regression and Logistic Regression
- Describe the difference between a correlation and regression analysis.
- Describe the assumptions and mechanics for estimating parameters in the simple and multiple linear regression models.
- Describe the logistic regression model, its key assumptions, and their implications.
- State the relationships between odds ratios and logistic regression coefficients.
- Derive the odds ratio between two groups defined by their predictor values.
Tuesday, November 1st 12:00 – 1:00 PM
#4 – Statistical Genetics: Classical to Modern
- Difference between linkage and association analysis
- Population concepts such as linkage disequilibrium and population stratification
- Copy number variation
- Quantitative Trait Locus (QTL) analysis
- Analysis with next-generation sequencing (RNA-seq)
Tuesday, November 8th 12:00 – 1:00 PM
#5 – Multi-item Scales and Tests: Development and Validation Methods
- Describe General Measurement Concepts and Methods
- Learn about Classical and Modern Test Theory
- Define Reliability and Validity
Tuesday, November 15th 12:00 – 1:00 PM
#6 – The Use of Item Response Theory (IRT) in Health
- Comparison of IRT to Classical Measurement Statistics
- How to interpret IRT and CAT statistics
- The use of IRT to create short forms and Computerized Adaptive Tests (CATs)
- How CATs are used in research and clinical settings
- How CATs are used to create tests of ability (including medical board exams)