Examining the design of statistical studies can help us answer Whitney Houston’s famous question, “How Will I Know?” How will I know if this new vaccine is effective, how will I know if a policy meets its stated goals, how will I know if evidence I gather is significant? I want to answer these questions in settings where data arise in clustered and correlated ways, including in COVID-19 studies. Understanding this data can help us design more efficient, more robust, and more meaningful clinical trials and research studies. And by understanding how statistical evidence is used in regulatory policy and the historical background of statistics, we can generate better evidence and communicate it better to a skeptical public.

Below, you can find brief descriptions and links to some of my research. If you have any questions, or have trouble accessing any of the articles, please reach out to me, at lkennedyshaffer (at) vassar (dot) edu.

COVID-19 Research

The COVID-19 pandemic has spurred an incredible amount of research in a wide variety of fields. To get the best evidence, we have to account for some of the unique features of data that come from infectious disease outbreaks. Accounting for these in the design and analysis of studies will improve the reliability of answers that we got and can even help us create more efficient studies that use these features to our advantage. Improving this evidence base will help policy and public health responses best address and end the pandemic.

Theory and Methods for Stepped-Wedge and Parallel-Arm Cluster-Randomized Trials

Research into clustered data and study design did not start with the COVID-19 pandemic. Clustered or correlated data can arise in many settings beyond infectious diseases, including policy evaluations, educational research, health systems research, and survey design. I work to understand the role of correlation and how we can best account for it in designing our studies.

History of Statistics and the Role of Statistics in Public Policy

Translational research is key to ensuring that statistics are properly used in fields as varied as public policy, business, law, and medicine, among others. I study how statistical methods, like p-values and significance testing, became so ubiquitous in certain areas, and what that means for how we develop, discuss, and disseminate new methods.

Fisher SMRW Table 2
R.A. Fisher, Statistical Methods for Research Workers, 1925. Harvard University Library.