Training Series

An Introduction to Clinical Research

The purpose of this online series of training videos is to provide introductory education materials for learners who are new to clinical research and collaboration. The goal is to give learners a general understanding of clinical research and data analysis to facilitate communication and collaboration with a quantitative expert, such as a biostatistician.

These videos contain standalone content, but can also serve as a prerequisite for in-person workshops that dive deeper into the topics presented and use real and applicable examples specific to the workshop audience. Videos are currently in development; please check back as we continue to add new videos as they are created.

Introduction to Research and Design 

  • The first video in our module introduces the general life cycle of clinical research. By the end of the video, learners will know the important characteristics that every research study should have, namely integrity, transparency, and reproducibility.

Formulating the Research Question (coming soon)

  • This video details how a scientific research question is developed. We also introduce the primary outcome of a research study, an important characteristic that has great impact on the entire study, including the study’s design, the number of individuals enrolled, and conclusions that can be drawn when the study ends.

The Null and Alternative Hypotheses (coming soon)

  • In this video, we discuss how to convert the scientific research question into a testable hypothesis, and explore the null and alternative components of a statistical hypothesis.

Study Design and Data Collection (coming soon)

  • This video broadly introduces study design and data collection. We discuss the two main types of research studies, how many individuals are needed for a research study, collecting raw data, and producing analysis datasets.

We will continue to add more videos as they are created. Tentative topics include the collaborative process, the Statistical Analysis Plan, descriptive data analyses and graphical displays, and inferential data analyses such as multivariable regression and survival analyses.

Module Archives

Below are some early modules that were developed and will eventually be replaced with the videos above. These use a journal article case study to illustrate concepts in clinical research.

Scientific Process I: Formulating the Question

  • This module introduces the first three steps of the scientific process: observing a phenomenon or pattern, formulating the scientific question, and developing the hypothesis.

Scientific Process II: Analysis and Inference

  • This module discusses sampling from a population of interest and the p-value – a quantity that permeates research but has limitations.

Scientific Process III: Design and Descriptive Analysis

  • This module describes power and sample size calculation for designing a study and common summary measures and graphical displays for exploring data.

The Statistical Analysis Plan

  • The Statistical Analysis Plan (SAP) is an important document that serves as a roadmap for the entire research project. This module highlights some of the key pieces of information needed in a SAP.

Survival Analysis I: Kaplan-Meier Estimator and Log Rank Test

  • Survival analyses are used when a researcher is interested in the amount of time it takes for some event to occur. This first model introduces this type of outcome and a key method of estimating the chance of being event-free over time. 

Survival Analysis II: The Cox Proportional Hazard Model

  • Survival analyses are used when a researcher is interested in the amount of time it takes for some event to occur. This second module covers the most common modeling technique used in survival analyses.

For more information Contact Tina:

Clemontina A. Davenport, PhD
Senior Biostatistician, BIOSTAT 702 Instructor
tina.davenport@duke.edu