Fall 2022 |
Topic |
Speaker |
Summary |
|
9/21/22 |
Prepare and Organize Data for Collaboration | Dr. David M. Kline | We will discuss ways to efficiently organize data so that it is machine-readable by statistical software and reduces the potential for errors. Software, like Excel, has many features to aid in organization of data and calculation of values of interest. However, data that appear organized and clear within a spreadsheet may not translate well into statistical software. These issues can create headaches for the statistician on the project and lead to delays in the processing and analysis of the data. |
| 10/5/22 | Study designs: experimental studies and prospective cohorts | Dr. Mike Bancks | This session provides an overview of the experimental and observational prospective cohort study designs and describes fundamental concepts of each and distinguishing methods. |
| 10/19/22 | Study designs: case-control, cross-sectional, and ecological studies |
Dr. Mike Bancks | This introductory-level session will provide an overview of the observational case-control, cross-sectional, and ecological study designs used in clinical and epidemiological research. Attendees will learn strengths and limitations of each design and potential application to their research interests. |
| 11/02/22 | Analysis of a discrete outcome |
Dr. Nathaniel O’Connell |
This introductory-level session will present the basic statistical concepts and approaches for analyzing outcome data with discrete or categorical form. |
| 11/16/22 | Navigating uncertainty with p-values and confidence intervals |
Dr. Morgana Mongraw-Chaffin |
This session for all levels will give in-depth and practical guidance on when, how, and why we use p-values and confidence intervals with many examples. |
| 12/07/22 | Mediation analysis methods |
Dr. Nathaniel O’Connell |
This introductory-level session will provide an overview of mediation analyses including basic methodology, statistics, and interpretation/inference. We will also discuss the fundamental strengths and limitations of this methodological approach. |
Spring 2023 |
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| 01/18/23 | Statistical Power: Understanding the inputs and how you come up with them | Dr. Walter Ambrosius |
This session will cover approaches to estimate statistical power, sample size, and effect estimates to be considered in the study design phase. |
| 02/01/23 | Interpretation of model input and output |
Dr. Hannah Ainsworth |
This introductory-level session will present fundamental aspects of statistical model building and interpretation. Material will cover types and operationalization of independent variables and covariates in the statistical model and how to interpret the coefficients from statistical models commonly used in clinical and population health. |
| 02/15/23 | Propensity score methodology | Dr. Ralph B. D`Agostino Jr |
This session will provide an introduction to propensity score methodology and discuss advantages of these statistical modeling techniques and how these approaches can be used. |
| 03/01/23 | Biostatistics: Analysis of a continuous outcome |
Dr. Heather M. Shappell |
This introductory-level session will present the basic statistical concepts and approaches for analyzing outcome data with continuous form. |
| 03/15/23 | Meta-analysis: Overview and comparison with integrative data analysis |
Dr. Edward Ip |
This session provides an overview of meta-analysis, a method to integrate information from multiple studies such as those extracted from systematic review, and discusses the pros and cons of meta-analysis and integrative data analysis. |
| 04/05/23 | Identifying and managing threats to validity: DAGS and other causal inference methods |
Dr. Mike Bancks |
This session will introduce approaches that can be used to identify and mitigate threats to validity in epidemiological and clinical research. |
| 04/19/23 | Interaction and effect modification: what are they and how are they different | Dr. Mike Bancks |
This moderate-to-advanced-level session will introduce, describe, and distinguish causal interaction and effect measure modification. |
| 05/03/23 | TBD |
Biostatistics, Epidemiology, and Research Design (BERD) Lunch and Learn Series
The Biostatistics, Epidemiology, and Research Design (BERD) groups at Wake Forest, Duke, and UNC are working together to share educational and training resources. The seminars are designed to provide researchers and aspiring researchers with tools and resources related to each of the BERD disciplines. The following seminars are shared across all three institutions. Sign-up and WebEx information for each seminar is at the bottom of the page.