In this course, experts will discuss the options a researcher must consider when embarking on clinical research. What research design should I choose? How do I start the process of getting my research approved? How will I analyze the data I collect? These are all important questions that a researcher faces.
We will discuss the key decisions a researcher needs to make when preparing for and conducting research, as well as tools for data analysis. You will learn what a pragmatic clinical trial is and how to calculate power and sample size for your study. You will also be exposed to more complex study designs sometimes used in pragmatic clinical trials, such as Bayesian and adaptive designs.
This course includes the following 11 lectures:
Overview of Design Options for Pragmatic Clinical Trials
Outcome Measures in Clinical Trials
Non-inferiority Trials
Basic Analytic Methods
Basic Power and Sample Size Calculations
SMART: Adaptive Treatment Strategies
Introduction to Bayesian Methods
Bayesian Designs
Quasi-Experiment in Health Services Research
Adaptive Trial Design
Logistics of Clinical Trials
This course is intended for anyone interested in comparative effectiveness research (CER) and patient-centered outcomes research (PCOR) methods.
This course is supported by grant number R25HS023214 from the Agency for Healthcare Research and Quality.
Syllabus
Overview of Design Options for Pragmatic Clinical Trials
Types of trial designs including randomized clinical trials
Sources of errors that could lead to erroneous trial results
Outcome Measures in Clinical Trials
Measuring health status and disease
Characteristics of a good outcome measure
Types of outcome measures in clinical trials
Non-inferiority Trials
Non-inferiority trial designs and how they differ from other designs
Interpretation and reporting of results
Basic Analytic Methods
Matching research questions with statistical analysis methods
Interpreting results
Distinguishing intent to treat from per protocol analyses
Problems with missing data
Basic Power and Sample Size Calculations
Relevant issues to estimate sample size in clinical trials
Interpreting study power
Calculating sample size using online calculators
SMART: Adaptive Treatment Strategies
Research questions which can benefit from an adaptive design
Analytic methods for adaptive designs
Interpreting results of adaptive designs
Introduction to Bayesian Methods
Statistical inference
Comparison of frequentist and Bayesian approaches and inference
Bayesian Designs
Bayesian method and adaptive design introduction
Adaptive randomization and predictive probability
Bayesian design trial interpretation
Software tools for conducting Bayesian designs
Quasi-Experiment in Health Services Research
Need for quasi-experiments and their limitations
Difference-in-Differences (DID) estimators and models