CERTaIN: Observational Studies and Registries
About this Course
While randomized controlled trials are considered to be the "gold standard" in health research, they cannot always be performed, for ethical or practical reasons. Observational studies gather information from data that has already been collected, or by observing and measuring patients' changes in health status and their response to interventions outside of a clinical trial. In this course, you will learn to identify the characteristics of observational studies, to interpret the results of observational studies, and to describe the use of health registries in comparative effectiveness research (CER). This course includes the following 11 lectures: Overview of Using Observational Data in Comparative Effectiveness Research (CER) Cancer Registries and Data Linkage SEER-Medicare and Other Data Sources Overview of Analytic Methods I Overview of Analytic Methods II Longitudinal Data Analysis Advanced Methods in CER I Advanced Methods in CER II Survival Analysis Analysis of Medical Cost Data in Observational Studies Healthcare Policy Research 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.Created by: The University of Texas MD Anderson Cancer Center in Houston
Level: Introductory
Related Online Courses
Le « Big Data » et l'UX vous interpellent? Ce MOOC vous donnera les méthodes et outils pour analyser le spectre des données traitées en UX, de l'analyse qualitative aux analytiques Web. Vous appr... more
Do big data and UX speak to you? This MOOC will give you the methods and tools to analyze the whole spectrum of data we handle in UX, from qualitative user research and quantitative user testing... more
Big data is transforming the health care industry relative to improving quality of care and reducing costs--key objectives for most organizations. Employers are desperately searching for... more
Statistical inference and modeling are indispensable for analyzing data affected by chance, and thus essential for data scientists. In this course, you will learn these key concepts through a... more
Please Note: Learners who successfully complete this IBM course can earn a skill badge — a detailed, verifiable and digital credential that profiles the knowledge and skills you’ve acquired in thi... more