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  2. Intention-to-treat analysis - Wikipedia

    en.wikipedia.org/wiki/Intention-to-treat_analysis

    Intention to treat analyses are done to avoid the effects of crossover and dropout, which may break the random assignment to the treatment groups in a study. ITT analysis provides information about the potential effects of treatment policy rather than on the potential effects of specific treatment. [citation needed]

  3. Average treatment effect - Wikipedia

    en.wikipedia.org/wiki/Average_treatment_effect

    The average treatment effect (ATE) is a measure used to compare treatments (or interventions) in randomized experiments, evaluation of policy interventions, and medical trials. The ATE measures the difference in mean (average) outcomes between units assigned to the treatment and units assigned to the control.

  4. Local average treatment effect - Wikipedia

    en.wikipedia.org/wiki/Local_average_treatment_effect

    In the presence of non-compliance, the ATE can no longer be recovered. Instead, what is recovered is the average treatment effect for a certain subpopulation known as the compliers, which is the LATE. When there may exist heterogeneous treatment effects across groups, the LATE is unlikely to be equivalent to the ATE.

  5. Principal stratification - Wikipedia

    en.wikipedia.org/wiki/Principal_stratification

    With a binary post-treatment covariate (e.g. attrition) and a binary treatment (e.g. "treatment" and "control") there are four possible strata in which subjects could be: those who always stay in the study regardless of which treatment they were assigned; those who would always drop-out of the study regardless of which treatment they were assigned

  6. Propensity score matching - Wikipedia

    en.wikipedia.org/wiki/Propensity_score_matching

    In the statistical analysis of observational data, propensity score matching (PSM) is a statistical matching technique that attempts to estimate the effect of a treatment, policy, or other intervention by accounting for the covariates that predict receiving the treatment.

  7. Difference in differences - Wikipedia

    en.wikipedia.org/wiki/Difference_in_differences

    Difference in differences (DID [1] or DD [2]) is a statistical technique used in econometrics and quantitative research in the social sciences that attempts to mimic an experimental research design using observational study data, by studying the differential effect of a treatment on a 'treatment group' versus a 'control group' in a natural experiment. [3]

  8. Division of Program Coordination, Planning, and Strategic ...

    en.wikipedia.org/wiki/Division_of_Program...

    The Division of Program Coordination, Planning, and Strategic Initiatives (DPCPSI) is a division of the Office of the Director of the National Institutes of Health of the United States of America. DPCPSI was formally established as part of implementing the requirements of the NIH Reform Act of 2006. [ 1 ]

  9. Risk Evaluation and Mitigation Strategies - Wikipedia

    en.wikipedia.org/wiki/Risk_Evaluation_and...

    Risk Evaluation and Mitigation Strategies (REMS) is a program of the US Food and Drug Administration for the monitoring of medications with a high potential for serious adverse effects. REMS applies only to specific prescription drugs, but can apply to brand-name or generic drugs. [1] The REMS program was formalized in 2007.