In this simulation of a doctor's office, students play the roles of …
In this simulation of a doctor's office, students play the roles of physician, nurse, patients, and time-keeper, with the objective to improve the patient waiting time. They collect and graph data as part of their analysis. This serves as a hands-on example of using engineering principles and engineering design approaches (such as models and simulations) to research, analyze, test and improve processes.
Reproducibility, Research Management Planning, Structuring a study, Preregistration + Analysis Plan, Files …
Reproducibility, Research Management Planning, Structuring a study, Preregistration + Analysis Plan, Files and Version Control, Sharing on the OSF, Incentives (Badges, RR)
Preregistration is the process of specifying project details, such as hypotheses, data …
Preregistration is the process of specifying project details, such as hypotheses, data collection procedures, and analytical decisions, prior to conducting a study. It is designed to make a clearer distinction between data-driven, exploratory work and a-priori, confirmatory work. Both modes of research are valuable, but are easy to unintentionally conflate. See the Preregistration Revolution for more background and recommendations.
For research that uses existing datasets, there is an increased risk of analysts being biased by preliminary trends in the dataset. However, that risk can be balanced by proper blinding to any summary statistics in the dataset and the use of hold out datasets (where the "training" and "validation" datasets are kept separate from each other). See this page for specific recommendations about "split samples" or "hold out" datasets. Finally, if those procedures are not followed, disclosure of possible biases can inform the researcher and her audience about the proper role any results should have (i.e. the results should be deemed mostly exploratory and ideal for additional confirmation).
This project contains a template for creating your preregistration, designed specifically for research using existing data. In the future, this template will be integrated into the OSF.
Preregistration is the process of specifying project details, such as hypotheses, data …
Preregistration is the process of specifying project details, such as hypotheses, data collection procedures, and analytical decisions, prior to conducting a study. It is designed to make a clearer distinction between data-driven, exploratory work and a-priori, confirmatory work. Both modes of research are valuable, but are easy to unintentionally conflate. See the Preregistration Revolution for more background and recommendations.
For research that uses existing datasets, there is an increased risk of analysts being biased by preliminary trends in the dataset. However, that risk can be balanced by proper blinding to any summary statistics in the dataset and the use of hold out datasets (where the "training" and "validation" datasets are kept separate from each other). See this page for specific recommendations about "split samples" or "hold out" datasets. Finally, if those procedures are not followed, disclosure of possible biases can inform the researcher and her audience about the proper role any results should have (i.e. the results should be deemed mostly exploratory and ideal for additional confirmation).
This project contains a template for creating your preregistration, designed specifically for research using existing data. In the future, this template will be integrated into the OSF.
Students learn how engineering design is applied to solve healthcare problems by …
Students learn how engineering design is applied to solve healthcare problems by using an engineering tool called simulation. While engineering design is commonly used to study and design everything from bridges, factories, airports to space shuttles, the use of engineering design to study healthcare administration and delivery is a relatively new concept.
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