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Intention-to-treat analysis. In medicine an intention-to-treat (ITT) analysis of the results of a randomized controlled trial is based on the initial treatment assignment and not on the treatment eventually received. ITT analysis is intended to avoid various misleading artifacts that can arise in intervention research such as non-random ...
Local average treatment effect. In econometrics and related empirical fields, the local average treatment effect (LATE), also known as the complier average causal effect (CACE), is the effect of a treatment for subjects who comply with the experimental treatment assigned to their sample group. It is not to be confused with the average treatment ...
However, by restricting the analysis to a selected patient population, it does not show all effects of the new drug. Further, adherence to treatment may be affected by other factors that influence the outcome. Accordingly, per-protocol effects are at risk of bias, whereas the intent-to-treat estimate is not. [7]
The extent to which the groups can be analyzed exactly as they existed upon randomization (i.e., whether a so-called "intention-to-treat analysis" is used). A "pure" intention-to-treat analysis is "possible only when complete outcome data are available" for all randomized subjects; [72] when some outcome data are missing, options include ...
Number needed to treat. Group exposed to a treatment (left) has reduced risk of an adverse outcome (grey) compared to the unexposed group (right). 4 individuals need to be treated to prevent 1 adverse outcome (NNT = 4). The number needed to treat (NNT) or number needed to treat for an additional beneficial outcome (NNTB) is an epidemiological ...
“The model that is geared toward alcoholism doesn’t effectively address heroin addiction,” Merrick said. “In a perfect world, we would have a 12-step model integrated with medically assisted therapy.” At least some of the top officials overseeing Kentucky’s response to the opioid epidemic are as open to medications as Merrick is.
Zelen's design is an experimental design for randomized clinical trials proposed by Harvard School of Public Health statistician Marvin Zelen (1927-2014). In this design, patients are randomized to either the treatment or control group before giving informed consent. Because the group to which a given patient is assigned is known, consent can ...
Regression discontinuity design. In statistics, econometrics, political science, epidemiology, and related disciplines, a regression discontinuity design (RDD) is a quasi-experimental pretest–posttest design that aims to determine the causal effects of interventions by assigning a cutoff or threshold above or below which an intervention is ...