Explore >> Select a destination
|
You are here 
|
www.publichealth.columbia.edu | ||
| | | | |
engineering.virginia.edu
|
|
| | | | | A team of University of Virginia researchers released the first-ever database of hurricane evacuation orders in the United States. | |
| | | | |
www.listendata.com
|
|
| | | | | This article explains the difference between standardized and unstandardized coefficients, with examples. | |
| | | | |
www.rdatagen.net
|
|
| | | | | Recently, we were planning a study to evaluate the effect of an intervention on outcomes for very sick patients who show up in the emergency department. My collaborator had concerns about a phenomenon that she had observed in other studies that might affect the results - patients measured earlier in the study tend to be sicker than those measured later in the study. This might not be a problem, but in the context of a stepped-wedge study design (see this for a discussion that touches this type of study design), this could definitely generate biased estimates: when the intervention occurs later in the study (as it does in a stepped-wedge design), the "exposed" and "unexposed" populations could differ, and in turn so could the outcomes. We might confuse an artificial effect as an intervention effect. | |
| | | | |
fharrell.com
|
|
| | | Historical data (HD) are being used increasingly in Bayesian analyses when it is difficult to randomize enough patients to study effectiveness of a treatment. Such analyses summarize observational studies' posterior effectiveness distribution (for two-arm HD) or standard-of-care outcome distribution (for one-arm HD) then turn that into a prior distribution for an RCT. The prior distribution is then flattened somewhat to discount the HD. Since Bayesian modeling makes it easy to fit multiple models at once... | ||
